Record 55

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Language Laboratory

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1 .LISTENING

1.1 BBC 1

CHARACTER SKETCH: CHARACTER CLIVE HARRIS DON BRADLEY KATE MECANA EDWARD GREEN JENNY ROSE SALIE GERALDINE DEREK JONES BOB & PETE

DESIGNATION MANAGING DIRECTOR SALES & MARKETING DIRECTOR HEAD OF SALES DEPARTMENT MARKETING EXECUTIVE HEAD OF ADMINISTRATION CLIVE’S SECRETARY RECEPTIONIST HEAD OF R&D DEPARTMENT RESEARCH ASSISTANTS

SCENE-1 GERALDINE

: Good morning Bibary systems, can I help you.

JENNY

: Good morning, GERALDINE.

GERALDINE

: Good morning, JENNY. Here is your newspaper and the post.

JENNY

: Thank you.

HARRIS

: Good morning JENNY, good week end.

JENNY

: Excellent thank you.

HARRIS

: So cold this morning

JENNY

: Very cold

HARRIS

: Good morning GERALDINE

GERALDINE

: Good morning Harris. Your newspaper and the post

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SCENE -2 JENNY

: Good morning, Kate

KATE

: Good morning JENNY .How are you?

JENNY

: I am fine, thank you

DON

: Good morning, JENNY

JENNY

: Good morning, Don

EDWARD

: Good morning. My name is Edward green. I am here to see Don Bradley.

GERALDINE

: Hey yes one minute please….Hello JENNY Edward green is in Reception.Please sit down.

EDWARD JENNY EDWARD JENNY EDWARD JENNY

: Thank you. : Are you Edward green? : Yes… : I am JENNY. Ross. How do you do? : Hello, Pleased to meet you. : Welcome to bribery systems.

EDWARD

: Thank you.

JENNY

: I am the head of administration in marketing department. My boss is Don Bradley well our boss is Don Bradley. Let me show you the department.

SCENE-3 JENNY

: This is the marketing department. This is my desk and that is Don’s office. He is not here at the moment. This is your desk, telephone, pc and pen drive. Let me take your coat.

EDWARD JENNY

: Thanks. :Over here is the stationary cupboard, papers, pencils, files etc. Help yourself for you need….Here is the photo copier and fax machine and here is the coffee machine. Would you like to have a cup of coffee?

EDWARD

: No thanks.

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SCENE-4 JENNY

: Kate, this is Edward green our new marketing executive.

KATE

: Ha, yes Edward .Hello welcome to Bibary systems marketing department. Excuse me….

EDWARD

: Hello Kate Mecana.

EDWARD

: What is Kate’s job?

JENNY

: She is head of sales….She is good.

EDWARD

: Where does she fit into the company’s structure?

JENNY

: Here is company’s marketing structure. You see Danny in the marketing structure and he is on the board, Kate reports to Don … you are here and you report to Don.

JENNY

: This is the board room. Here we have a range of products i.e. toys. Come on lets go to R&D workshop.

EDWARD

: I am sorry, R&D?

JENNY

: That’s research and development.

EDWARD

: Ha right.

SCENE-5 GERALDINE JENNY

: Thank you for calling good bye… : The managing director’s office is on first floor…Clive Harris….we call him Clive. This is Clive secretary Sally...

EDWARD

: Hello JENNY and you have met our receptionist GERALDINE

GERALDINE

: Hi

JENNY

: So, this research and development department. This is Bob and Peat…They are research assistants and through here is Derek Jones office. He has a team of six people…Derek, this is Edward Green our new…

DEREK

: Please…

JENNY

: I think you’re busy, sorry.

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DEREK

: No, please wait…ya finished…Good…Do you like it?

EDWARD

: What is it?

DEREK

: It is a toy, it’s a new electronic toy.

EDWARD

: It’s very good….Edward Green, pleased to meet you.

DEREK

: Derrick Jones welcome to bribery systems.

EDWARD

: Thank you.

SCENE-6 DON

: Edward Green starts today. He is the new marketing executive.

CLIVE

: Oh yes… Is he good?

DON

:I don’t know.. He is young, intelligent, he is well qualified but of course he has

no

experience. DEREK

: So that’s the exciting product range. This is the very new product. In fact this is a prototype.

EDWARD

: What is it?

DEREK

: It is called the Big Boss…

EDWARD

: Big boss! What does it do?

DEREK

: Ha Ha Ha…Say Hello Big Boss

EDWARD

: Hello Big Boss.

DEREK

: No No … into the microphone.

EDWARD

: Hello Big Boss

DEREK

: Try again.

EDWARD

: Hello Big Boss

BIG BOSS

: Hi Edward, welcome to bribery systems.

CLIVE

: what do you think Don

DON

: I don’t like this design.

CLIVE

: I agree, its not good… I like this one… He is angry.

DON

: Yes I think he is very funny…

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DEREK

: What do you think..?

EDWARD

: What about glasses?

DEREK

: That’s very good ,good idea, brilliant.

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1. LISTENING 1.2 BBC 2

CHARACTER SKETCH: CHARACTER

DESIGNATION

PHIL WATSON

MARKETING DIRECTOR

DON BRADLEY

SALES & MARKETING DIRECTOR

KATE MECANA

HEAD OF SALES DEPARTMENT

EDWARD GREEN

MARKETING EXECUTIVE

JENNY ROSE

HEAD OF ADMINISTRATION

GERALDINE

RECEPTIONIST

DEREK JONES

HEAD OF R&D DEPARTMENT

SMITH

MANAGING DIRECTOR RUYJ AGENCY

SAKAI

JAPANESE PARTNER

SCENE-1 EDWARD GREEN

: My name is Edward Green. I would like to speak to Mr. Smith.

RECEPTIONIST

: I am sorry. Mr. Smith isn’t available.

EDWARD GREEN

: Ok. I will ring back. Does Mr. Smith have a direct line?

RECEPTIONIST

: I am sorry, but the number is confidential.

EDWARD GREEN

: Ok Thank You.

SCENE-2 JENNY EDWARD GREEN

: It’s very difficult to speak to Mr. Smith. : Yes. I know.

SCENE-3 GERALDINE

: Good Morning. RUYJ advertising.

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DON BRADLEY

: Good morning. This is Don Bradley. Can I talk to Phil Watson? Please.

GERALDINE

: What company are you from?

DON BRADLEY

: Bibary Systems.

GERALDINE

:

I will put you through

SCENE-4 DON BRADLEY

: Good Morning. Can I talk to Phil please?

RECEPTIONIST

: Can I ask who is calling.

DON BRADLEY

: Don Bradley from Bibary Systems.

RECEPTIONIST

: Well Mr. Bradley, I am afraid Phil is not in the office at the moment. Can I take the message or would you like to ring him on his mobile phone.

DON BRADLEY

: I will try his mobile. Can I have the number please?

RECEPTIONIST

: 080254377.

DON BRADLEY

: Just let me check that 080254377.

RECEPTIONIST

: That’s it.

DON BRADLEY

: Thanks.

SCENE-5

PHIL WATSON

: Hello, Phil Watson

DON BRADLEY

: Hello Phil, this is Don Bradley.

PHIL WATSON

: Hello Don, sorry to keep you waiting. How are you?

DON BRADLEY

: I am fine, thanks. Can we meet, we have a new product and I want you to see it.

SCENE-6 RECEPTIONIST EDWARD GREEN

: Hello, Mr. Smith’s office. : Hello, My name is Edward Green from Bibary System. I rang earlier. I would like to speak to Mr. Smith please.

RECEPTIONIST

: I am afraid. Mr. Smith isn’t in the office at the moment. Can I ask what it is about?

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EDWARD GREEN

: It is very important. I represent Bibary Systems. We have got a new Product and I want Mr. Smith to see it.

RECEPTIONIST

: Please send the product specifications by mail Mr. Green.

EDWARD GREEN

: I would like Mr. Smith to see the product and would like to talk to Mr. Smith direct. When is the good time to call?

RECEPTIONIST

: You could try ringing this afternoon.

EDWARD GREEN

: Thank You. Good Bye

SCENE-7 CALLER

: Yes, Can I speak to Peter.

DERRICK

: Peter hill?

CALLER

: No. Peter Toyoma.

DERRICK

: There is no one here called Peter Toyoma.

CALLER

: Is that extension 367.

DERRICK

: No. You have got the wrong number. This is 412.

CALLER

: I’m sorry. Could you please connect me to the switch board?

DERRICK

: Yes. Hang on.

SCENE-8 EDWARD GREEN

:Hello. This is Edward Green. I rang earlier. I would like to speak to Mr. Smith pleases.

RECEPTIONIST

: I am afraid. Mr. Smith is in meeting.

EDWARD GREEN

: Is he free later this afternoon.

RECEPTIONIST

: I don’t think so. Mr. Smith is very busy at the moment.

EDWARD GREEN

: I will ring again tomorrow.

RECEPTIONIST

: I am afraid. Mr. Smith isn’t in the office tomorrow.

SCENE-9 GERALDINE

: Good Morning, Bibary Systems. How can I help you?

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SAKAI

: Hello, My name is Sakai. I would like to speak to Mr. Harris please.

GERALDINE

: Please hold the line Mr.Sakai. I will put you through.

HARRIS

: Hello.

GERALDINE

: Mr.Sakai is on the line.

HARRIS

: Put him through.

HARRIS

: Hello, Mr.Sakai.

SAKAI

: Hello, Mr. Harris. How are you?

HARRIS

: I am very well. Thank you. How are you?

SACHAI

: I am fine. I am calling about our meeting.

HARRIS

: Yes.

SCENE-10 JENNY

: Good Night Edward.

EDWARD GREEN

: Good Night. I am going to phone Mr. Smith number once again.

JENNY

: Good Luck.

EDWARD GREEN

: Its 6’o clock. May be Mr. Smith is still at work. May be his secretary Isn’t there.

JENNY

: I don’t think….

EDWARD GREEN

: Just wait.

SCENE-11 EDWARD GREEN

: Ah! Mr. Smith.. My name is Edward Green.

MR.SMITH

: Yes.

EDWARD GREEN

: You don’t know me but I work in Don Bradley’s office at Bibary System.

MR.SMITH

: Yes

EDWARD GREEN

: I spoke to your secretary today.

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MR.SMITH

: Yes

EDWARD GREEN

: You publish your catalogue this month. And we have an exciting new Product.

MR.SMITH

: I have all the products I need.

EDWARD GREEN

: I would like you to have a word with Big Boss.

MR.SMITH

: I am sorry….

EDWARD GREEN

: I will put our new product on the line now.

BIG BOSS

: Hello, Mr. Smith. My name is Big Boss. I am 18 inches high. I am voice activated. And I want to be in your catalogue.

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1 .LISTENING 1.3 BBC 3

CHARACTER SKETCH: CHARACTER CLIVE HARRIS DON BRADLEY KATE MECANA EDWARD GREEN JENE ROSE SALIE GERALDINE DEREK JONES BOB & PETE

DESIGNATION MANAGING DIRECTOR SALES & MARKETING DIRECTOR HEAD OF SALES DEPARTMENT MARKETING EXECUTIVE HEAD OF ADMINISTRATION CLIVE’S SECRETARY RECEPTIONIST HEAD OF R&D DEPARTMENT RESEARCH ASSISTANTS

SCENE 1: EDWARD

: So Mr. Smith when can we meet?

SMITH

: I am busy the whole week.

EDWARD

: Maybe the week after,

SMITH

: Talk to my secretary.

EDWARD

: You print your catalogue this month don’t you?

SMITH

: Yes.

EDWARD

: Could you possibly see the product this week? It won’t take long.

SMITH

: Ok. Be here on Wednesday morning 8 sharp! I’ll give you 20 minutes.

EDWARD

: Thank your Mr. Smith! I’ll see you on Wednesday morning at 8’ o clock.

JENNY

: Well done!

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SCENE 2: HARRIS

: Good morning Geraldine!

GERALDINE

: Good morning Mr. Harris!

HARRIS

: Jenny! Could you ring up Mr. Sakaai‘s office in Japan? We need to set up a meeting. Not this week, but the meeting must be before November the 3rd. I would like Kate, Don Bradley and Derek to be There. Clive Harris!

DEREK

: Clive! It’s Derek!

HARRIS

: Hello Derek! What can I do for you?

DEREK

: Could you come down to the development workshop for a second?

HARRIS

: Derek… I am busy!

DEREK

: Come on! It’ll take five minutes.

HARRIS

: Alright! I’ve got five minutes. I am seeing Kate Mc Anna at 11.

JENNY

: Hello! Could I speak to Mr. Sakaai’s secretary? This is Jenny from Bibary systems in the UK. Mr. Harris would like to arrange a meeting with Mr. Sakaai. I wonder if you can check Mr. Sakaai’s European itenerary.

SCENE 3: GERALDINE

: Yes….yes…yes… I’ll make sure he gets the message. Alright Goodbye. Mr. Harris I just got a call from Mr. Peter’s secretary. I am afraid he is going to be fifteen minutes late for his appointment this afternoon.

HARRIS

: Ok! That’s no problem.

GERALDINE

: Good morning. Bibary systems…well…. Mr. Green can see you at 11 o’clock on Monday. Is that alright? No I am sorry.. on Tuesday He has a meeting in the morning. Is the afternoon possible? Alright!

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Thank you! Hello Bibary systems!

SCENE 4: DEREK

: What do you think?

HARRIS

: We’ll miss the launch date!

DEREK

: No! it’ll be on schedule.

HARRIS

: February the 15th?

DEREK

: It will be ready on February the 15th.

HARRIS

: We must meet the deadline.

SCENE 5: JENNY

: Kate… have you got a minute?

KATE

: What‘s wrong Jenny?

JENNY

: I have a problem. I am trying to arrange a meeting with Mr. Sakaai. He is in the UK for these 3 days, the 1st, the 2nd and the 3rd of November. But he is only available on the 1st and the 2nd. That’s the Monday and the Tuesday. Clive Harris is in Scotland on the Tuesday and Don cant make it Monday morning and u and Derek are both in meetings on Monday afternoon. What am I to do?

KATE

: Set up an evening meeting.

JENNY

: No… Sakaai’s secretary says he has dinner engagements on the 2nd and the 3rd.

KATE

: Monday evening?

JENNY

: Mr. Sakaai arrive at the airport at 9’o clock on Monday morning and it Is a 9 hour flight. Monday evening is not a good time for the meeting. He will be jet lagged.

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KATE

: Then Derek and I will have to change our arrangements. May I see my diary? Change our 10’o clock meeting with Mr. Clarke. Make it at half past 8 on the 4th.

JENNY

: You are giving a dinner party on the 4th.

KATE

: 8:30 AM… not 8:30 PM.

JENNY

: That’s going to be a long day!

SCENE 6: EDWARD

: Good morning!

JENNY

: Hi Edward! How is it going?

EDWARD

: Its going very well!!

KATE

: You look very happy!

EDWARD

: I am happy! I met Mr. Smith this morning at 8.30.!

KATE

: That’s very good!! And??

EDWARD

: Mr.Smith liked Big Boss!

KATE

: Good!

EDWARD

: But he didn’t like the name.

KATE

: Why not?

EDWARD

: He says Big Boss isn’t a good name! he wants to call it Tycoon Tim. But he thinks Big Boss will sell!

KATE

: Well done! Its your first marketing success!

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1. LISTENING AND COMPREHENDING 1.2. LP1 1. Would you like to join us for lunch? 2. The teacher intended to return the paper, but she left them at home. 3. When do you expect to start your new job? 4. Because the sun was in a rise we had to wear dark glasses. 5. The bus is scheduled to stop here every quarter hour. 6. You will have to make up your mind soon because the dead line is day after tomorrow. 7. How long does it take you to get a work? 8. No matter how hard I look, I can’t see the bird singing on the tree. 9. What is the fastest way of going to California? 10. Louis mailed the letter in January but it did not reach Bolivia until March. 11. Why hasn’t your garden grown well this year? 12. With only 10 second remaining in the game the player seized the ball from his opponent and made a goal. 13. Ed was about to shut the door, when the phone rang. 14. What would you have done if the teacher had asked you about economics? 15. The flight arriving from Kuwait due at 5:30 will be 20 minutes late. 16. Can you tell me which of those buildings is the Bank? 17. There won’t be any seats left for the Basket ball tonight. 18. To sell more goods many stores are now staying open late at night. 19. How do you find living in the city? 20. Modern washing machines have greatly reduced the amount of work that doing laundry requires. 21. Which of the girls would you like to have accompanied us? 22. I’m not too sure I understand what your problem is? 23. Richard was hardly working at all, when the Supervisor opened the door.

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24. Even though we arrived at the theatre late, the play hadn’t begun yet. 25. He has been looking for a better paying job for the last two months, but still hasn’t found one.

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1.3 READING COMPREHENSION The pioneers of the teaching of science imagined that its introduction into education would remove the conventionality, artificiality, and backward-lookingness which were characteristic of classical studies, but they were gravely disappointed. So, too, in their time had the humanists thought that the study of the classical authors in the original would banish at once the dull pedantry and superstition of mediaeval scholasticism. The professional schoolmaster was a match for both of them, and has almost managed to make the understanding of chemical reactions as dull and as dogmatic an affair as the reading of Virgil's Aeneid. The chief claim for the use of science in education is that it teaches a child something about the actual universe in which he is living, in making him acquainted with the results of scientific discovery, and at the same time teaches him how to think logically and inductively by studying scientific method. A certain limited success has been reached in the first of these aims, but practically none at all in the second. Those privileged members of the community who have been through a secondary or public school education may be expected to know something about the elementary physics and chemistry of a hundred years ago, but they probably know hardly more than any bright boy can pick up from an interest in wireless or scientific hobbies out of school hours. As to the learning of scientific method, the whole thing is palpably a farce. Actually, for the convenience of teachers and the requirements of the examination system, it is necessary that the pupils not only do not learn scientific method but learn precisely the reverse, that is, to believe exactly what they are told and to reproduce it when asked, whether it seems nonsense to them or not. The way in which educated people respond to such quackeries as spiritualism or astrology, not to say more dangerous ones such as racial theories or currency myths, shows that fifty years of education in the method of science in Britain or Germanyhas produced no visible effect whatever. The only way of learning the method of science is the long and bitter way of personal

experience, and, until the

educational or social systems are altered to make this possible, the best we can expect is the production of a minority of people who are able to acquire some of the techniques of science and a still smaller minority who are able to use and develop them.

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1. The author implies that the 'professional schoolmaster’ has A. no interest in teaching science B. thwarted attempts to enliven education C. aided true learning D. supported the humanists E. been a pioneer in both science and humanities. 2. The author’s attitude to secondary and public school education in the sciences is A. ambivalent B. neutral C. supportive D. satirical E. contemptuous 3. The word ‘palpably’ most nearly means A. empirically B. obviously C. tentatively D. markedly E. ridiculously 4. The author blames all of the following for the failure to impart scientific method through the education system except A. poor teaching B. examination methods C. lack of direct experience D. the social and education systems E. lack of interest on the part of students

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5. If the author were to study current education in science to see how things have changed since he wrote the piece, he would probably be most interested in the answer to which of the following questions? A. Do students know more about the world about them? B. Do students spend more time in laboratories? C. Can students apply their knowledge logically? D. Have textbooks improved? E. Do they respect their teachers?

6. ‘Astrology’ is mentioned as an example of A. a science that needs to be better understood B. a belief which no educated people hold C. something unsupportable to those who have absorbed the methods of science D. the gravest danger to society E. an acknowledged failure of science 7. All of the following can be inferred from the text except A. at the time of writing, not all children received a secondary school education B. the author finds chemical reactions interesting C. science teaching has imparted some knowledge of facts to some children D. the author believes that many teachers are authoritarian E. it is relatively easy to learn scientific method.

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1.4 EDITING 1. I has suffered from acute asthma for twenty years. Error Reason

:have :the verb should agree with the subject in person and number

Correction

:I have suffered from acute asthma for twenty years.

2. The company president has taken steps to ensure that she can handle the pressure and anxiety associated with the job, including joining a yoga class and enlisting the support of a network of friends. Error

: company

Reason

:error in possessive case.

Correction

: The Company’s president has taken steps to ensure that she can

handle the pressure and anxiety associated with the job .

3. union insisted on an increase in their members’ starting pay, and threatened to call a strike if the company refused to meet the demand Error

:the

Reason

:error in article

Correction :The union insisted on an increase in their members’ starting pay, and threatened to call a strike if the company refused to meet their demand

4. Television viewers claim that the number of scenes depicting alcohol consumption have increased dramatically over the last decade. Error Reason Correction

:have :error in subject verb agreement :Television viewers claim that the number of scenes depicting alcohol

consumption has increased dramatically over the last decade 5. Employees with less personal problems are likely to be more productive.

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Error

:lesser

Reason

:Error in comparative degree

Correction

:Employees with lesser personal problem are likely to be more productive

6.

The three richest men in Americahave assets worth more than the combined assets of the sixty poorest countries of the world. Error

:poorest

Reason

:error in adjective.

Correction

: The three richest men in America have assets worth more than the combined assets of the sixty poor countries of the world.

7. Shipwrecked on a desert island, coconuts and other fruits formed the basis of the sailor’s diet. Error

:desert island

Reason Correction

:spelling mistake :shipwrecked on a deserted island, coconuts and other fruits formed the basis of the sailor’s diet

8. Fifty percent of the people alive today have never made a phone call, but thirty percent still have no electricity connections to their homes. Error Reason

:but :Error in subject verb agreement

Correction

:Fifty percent of the people alive today has never made a phone call and thirty percent still has no electricity connections to their homes.

9. The farmer should not have been so careless as to leave the door of the house unbolted when he had gone to bed. Error

: as

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Reason Correction

:omission of as. :The farmer should not have been so careless to leave the door of the house unbolted when he had gone to bed.

10.

The engineer, who is renowned for his ingenuity , has designed a very unique cooling system for our new plant in Spain. Error

:very unique

Reason Correction

:redundancy error. :The engineer, who is renowned for his ingenuity , has designed a unique cooling system for our new plant in Spain.

11. The students have discovered that they can address issues more effectively through letter-writing campaigns and not through public demonstrations. Error

: and not through

Reason Correction

: redundancy error. : The students have discovered that they can address issues more effectively through letter-writing campaigns than through public demonstrations.

12. After hours of futile debate, the committee has decided to postpone further discussion of the resolution until their next meeting. Error

: until

Reason

: Error in subject verb agreement

Correction

: After hours of futile debate, the committee have decided to postpone

further discussion of the resolution till their next meeting.

13. I lie down and sleep every night.

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Error

: lie down and

Reason Correction

: error in word. : I lay down to sleep every night.

14. Last Monday I will have bought four bushels of corn. Error

: Last Monday I will

Reason Correction

: Error in tense : Last Monday I bought four bushels of corn

15. The students at King High are smartest than the students at Lincoln High. Error

: smartest

Reason Correction

: Error in degree of comparison : The students at King High are smarter than the students at Lincoln High.

16. If you want to arrive on time you better leave quickly. Error

: quick

Reason Correction

: Error in adverb. : If you want to arrive on time you better leave quickly.

17. I told him that he did a well job on the assignment. Error Reason Correction

: well : Error in adjective : I told him that he did a good job on the assignment

18. He said that I should really start to instruct the kids, including to teach them reading. Error Reason Correction

: instruct and to teach : Gerund : He said that I should really start to instructing the kids, including to teaching them reading

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I cannot except any kind of personal check.

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Error Reason Correction

: except : word error : I cannot accept any kind of personal check.

20. There are many affects of global warming that are starting to show up. Error

: affects

Reason

: word error.

Correction

: There are many effects of global warming that are starting to show up.

21. I ain’t going to listen to her anymore. Error

: ain’t

Reason Correction

: Error in verb. : I am not going to listen to her anymore.

22. He use to be my friend. Error Reason Correction

: use to : Error in verb. : He used to be my friend.

23. Irregardless of your opinion on abortion, you must admit that there are many perspectives in the debate. Error Reason Correction

: Irregardless : Error in spelling . : Regardless of your opinion on abortion, you must admit that there are many perspectives in the debate.

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24. One should do his/her duty Error

: his/her

Reason

: Error in subject verb agreement.

Correction

: One should do one’s duty

25. You aren’t suppose to mess with her Error

: suppose

Reason Correction

26.

:past participle should be used : You aren’t supposed to mess with her

Reading is my favourite hobby even though to play baseball is Joseph’s. Error

: to play

Reason

: gerund

Correction

: Reading is my favourite hobby although to play baseball is Joseph’s.

27. I walk in the street Error

: walk

Reason Correction

: preposition : I walk along the street

. 28. Everyone are excited about the party next weekend, and I am definitely one of the people who are going. Error

: are

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Reason Correction

: concord : Everyone is excited about the party next weekend, and I am definitely one of the people who are going.

29.

Here's some good advise for students who want to find the perfect internship Error Reason Correction

: advise :verb is used instead of noun(spelling) : Here is some good advice for students who want to find the perfect internship.

30. Talent develops in quiet places. Error Reason Correction

: Talent develops : subject verb : Talents develop in quiet places.

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CAREER LAB

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2.1. PRESENTATION 2.1.1 RELATIONSHIP

Good morning to everyone present here. I’m going to share my views on “Relationship”. Anything in this world can’t survive on its own. Each one has to depend upon some another for its existence. Relationship between two comes into existence when an invisible bond has came into existence between them. With this invisible bond they both come into synchronization where both know about the whereabouts of another. Relationship can be of many kinds •

Relationship between two non-living things-mouse and a monitor.

•

Relationship between a living and non-living thing-car and its owner.

•

Relationship between living things.

Let us see about the relationship between human beings. It’s more complicated as we humans live in a nut-shell and we do not come out of it so soon .My dad always has a good relationship with everyone around him, no matter what the person’s background is. As a little boy I have always wondered why my dad wants to get closer to everyone. But after finishing my school, I moved away from my native and I had to face the world outside my house alone. Now I know the value of maintaining a relationship with people of different stratus. It gives us an edge over others, take some extra credits and so on. Imagine a world where you have no relationship other than your blood relationship, you will find out how important relationships are very much essential for a healthy and peaceful living .We all know that we do not have a cardinal relationship with our neighboring country Pakistan and that makes us to face so many problems. The same applies with ordinary human beings. If we don’t have a cardinal relationship with our neighbor, that makes our home a living hell. I can still remember the day when I stepped in my class two years ago, I had some 50 odd alien-looks around me. No one had any idea about others and we all were from different background. As days rolled over we all came together knowing each others. But we went in groups in which we are comfortable with, who all shared similar views. So if you ask our class as a whole ’Are you all united?’, the answer will be a NO. I’m pretty sure that if I step into the third year class I still get about a 5-10 alien-looks. It’s not that we are rivalries but we live in a nut-shell and we don’t want to come out of it. What we are doing is a big mistake and we must rectify it. We should have a cardinal relationship with everyone around us no matter what the differences may be. If we don’t do that we may not loose anything but if we do it we might have the biggest gain.

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2.1. PRESENTATION 2.1.2 SPEECH RECOGNITION

INTRODUCTION Speech recognition (also known as automatic speech recognition or computer speech recognition) converts spoken words to machine-readable input (for example, to key presses, using the binary code for a string of character codes). The term "voice recognition" is sometimes incorrectly used to refer to speech recognition, when actually referring to speaker recognition, which attempts to identify the person speaking, as opposed to what is being said. Confusingly, journalists and manufacturers of devices that use speech recognition for control commonly use the term Voice Recognition when they mean Speech Recognition.

OVERVIEW In this section, the history, the models, and the applications of speech recognition software are discussed. The terms defined in this section are only those that have special significance in speech recognition.

HISTORY One of the most notable domains for the commercial application of speech recognition in the United States has been health care and in particular the work of the medical transcriptionist (MT). According to industry experts, at its inception, speech recognition (SR) was sold as a way to completely eliminate transcription rather than make the transcription process more efficient, hence it was not accepted. It was also the case that SR at that time was often technically deficient. Additionally, to be used effectively, it required changes to the ways physicians worked and documented clinical encounters, which many if not all were reluctant to do. The biggest limitation to speech recognition automating transcription, however, is seen as the software. The nature of narrative dictation is highly interpretive and often requires judgment that may be provided by a real human but not yet by an automated system. Another limitation has been the extensive amount of time required by the user and/or system provider to train the software.

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A distinction in ASR is often made between "artificial syntax systems" which are usually domain-specific and "natural language processing" which is usually languagespecific. Each of these types of application presents its own particular goals and challenges.

Hidden Markov model (HMM)­based speech recognition Modern general-purpose speech recognition systems are generally based on Hidden Markov Models. These are statistical models which output a sequence of symbols or quantities. One possible reason why HMMs are used in speech recognition is that a speech signal could be viewed as a piecewise stationary signal or a short-time stationary signal. That is, one could assume in a short-time in the range of 10 milliseconds, speech could be approximated as a stationary process. Speech could thus be thought of as a Markov model for many stochastic processes. Another reason why HMMs are popular is because they can be trained automatically and are simple and computationally feasible to use. In speech recognition, the hidden Markov model would output a sequence of n-dimensional real-valued vectors (with n being a small integer, such as 10), outputting one of these every 10 milliseconds. The vectors would consist of cepstral coefficients, which are obtained by taking a Fourier transform of a short time window of speech and decorrelating the spectrum using a cosine transform, then taking the first (most significant) coefficients. The hidden Markov model will tend to have in each state a statistical distribution that is a mixture of diagonal covariance Gaussians which will give likelihood for each observed vector. Each word, or (for more general speech recognition systems), each phoneme, will have a different output distribution; a hidden Markov model for a sequence of words or phonemes is made by concatenating the individual trained hidden Markov models for the separate words and phonemes. Described above are the core elements of the most common, HMM-based approach to speech recognition. Modern speech recognition systems use various combinations of a number of standard techniques in order to improve results over the basic approach described above. A typical large-vocabulary system would need context dependency for the phonemes (so phonemes with different left and right context have different realizations as HMM states); it would use cepstral normalization to normalize for different speaker and recording conditions; for further speaker normalization it might use vocal tract length normalization (VTLN) for male-female normalization and maximum likelihood linear regression (MLLR) for more general speaker adaptation. The features would have so-called delta and delta-delta coefficients to capture speech dynamics and in addition might use heteroscedastic linear

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discriminant analysis (HLDA); or might skip the delta and delta-delta coefficients and use splicing and an LDA-based projection followed perhaps by heteroscedastic linear discriminant analysis or a global semitied covariance transform (also known as maximum likelihood linear transform, or MLLT). Many systems use so-called discriminative training techniques which dispense with a purely statistical approach to HMM parameter estimation and instead optimize some classification-related measure of the training data. Examples are maximum mutual information (MMI), minimum classification error (MCE) and minimum phone error (MPE). Decoding of the speech (the term for what happens when the system is presented with a new utterance and must compute the most likely source sentence) would probably use the Viterbi algorithm to find the best path, and here there is a choice between dynamically creating a combination hidden Markov model which includes both the acoustic and language model information, or combining it statically beforehand (the finite state transducer, or FST, approach).

Dynamic time warping (DTW)-based speech recognition Dynamic time warping is an approach that was historically used for speech recognition but has now largely been displaced by the more successful HMM-based approach. Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed. For instance, similarities in walking patterns would be detected, even if in one video the person was walking slowly and if in another they were walking more quickly, or even if there were accelerations and decelerations during the course of one observation. DTW has been applied to video, audio, and graphics – indeed, any data which can be turned into a linear representation can be analyzed with DTW. A well known application has been automatic speech recognition, to cope with different speaking speeds. In general, it is a method that allows a computer to find an optimal match between two given sequences (e.g. time series) with certain restrictions, i.e. the sequences are "warped" non-linearly to match each other. This sequence alignment method is often used in the context of hidden Markov models.

Performance of speech recognition systems The performance of speech recognition systems is usually specified in terms of accuracy and speed. Accuracy may be measured in terms of performance accuracy which is usually rated with word error rate (WER), whereas speed is measured with the real time factor. Other measures of accuracy include Single Word Error Rate (SWER) and Command Success Rate (CSR). Most speech recognition users would tend to agree that dictation machines can achieve very high performance in controlled conditions. There is some confusion, however, over the interchangeability of the terms "speech recognition" and "dictation".

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Commercially available speaker-dependent dictation systems usually require only a short period of training (sometimes also called `enrollment') and may successfully capture continuous speech with a large vocabulary at normal pace with a very high accuracy. Most commercial companies claim that recognition software can achieve between 98% to 99% accuracy if operated under optimal conditions. `Optimal conditions' usually assume that users: •

have speech characteristics which match the training data,

•

can achieve proper speaker adaptation, and

•

work in a clean noise environment (e.g. quiet office or laboratory space).

This explains why some users, especially those whose speech is heavily accented, might achieve recognition rates much lower than expected. Speech recognition in video has become a popular search technology used by several video search companies. Limited vocabulary systems, requiring no training, can recognize a small number of words (for instance, the ten digits) as spoken by most speakers. Such systems are popular for routing incoming phone calls to their destinations in large organizations. Both acoustic modeling and language modeling are important parts of modern statistically-based speech recognition algorithms. Hidden Markov models (HMMs) are widely used in many systems. Language modeling has many other applications such as smart keyboard and document classification

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2.2 INTERVIEW QUERY 1. Tell me about yourself? I’m Vignesh GM from Salem. I finished my schooling in Bharathi Vidhya Bhavan, Erode. And at present I’m pursuing my Bachelor’s degree in Information Technology in Kumaraguru college of Technology, Coimbatore. To say about my areas of interest, I’m very much interested in program designing & problem solving. I have always been fascinated has brought me here in front of you all. I have a very strong belief that nothing succeeds than success and I can never ever comprise with anything lesser than success. Finally I would like to convey my gratitude to all panel members for giving me an opportunity to introduce myself.

2. Why are you applying for this particular job? As I have mentioned already my fascination for problem solving has made me sit in front of this panel. This fascination had driven me to qualify myself technically strong and it still drives me to upgrade myself in every opportunity I get. I have always tried to follow my dreams and this job would mark the commencement for making my dream a reality.

3. What do you know about our company? I know all the research activities carried out by this renowned company. The project in the field which other companies dare to do is all done in this prominent concern. There is no IT based article which does not appreciate the concern's project and software. From I recent interview of the M.D. of the company in RD I have learnt that he is trying hard to maintain a warm employee-employer relationship.

4. What make you qualified for this particular job? I strongly believe that my desire and fascination for programming is my most important qualification. This qualification has made me develop all the qualifications that I have mentioned in my resume. I have done a lot of paper presentations and have bagged a lot of prizes. I have done four project works. A project on ‘Speech recognition Software’ was done with the assistance of your R&D department.

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5. What can you do for us that someone else can’t? I think my motto, ‘Nothing succeeds than success’ makes me unique. I will try hard to give you 100% success ratio.

6. Why should we hire you? I have a very high profile educational qualification. I have always been one of the outstanding candidates where ever I go. I’m unique and I can do for you that someone else can’t. If I were in your panel I would consider a candidate with my calibre as a natural choice for the job. I’m the kind of person who will say “I don’t know the answer”, if don’t know the answer. But I know how to find the answer I will not give up until I find the answer.

7. What do you look for in a job? New challenges every day that drains my resources often so that I can develop my resources. A warm working environment and of course a reasonable salary.

8. Why are you looking to make a carrier change? I am looking to make carrier change because I have a keen interest in developing projects in different fields. I am very much interested in the new carrier as I want to be more exposure in the software techniques.

9. Why did you leave your last job? My last job was quite satisfactory in terms of the money that I was making. But it was not challenging. Over a period of time I found it monotonous and boring.

10. Why do you want to work for us? I want to work for this company as this is a renowned company. I believe that the company has efficient infrastructure to cope up with today's requisites. The work culture of this company is the culture which I am looking for. Your R & D department has made me really interested to work for your company.

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11. How long will it take you to start making a meaningful contribution? Well it will take at least a couple of days to get used to the new working environment. A couple of days to know the nature of my job and a couple more to get started. That sums up a week I guess.

12. What are your strengths? My commitness to the job given to me is my strength I guess. I always associate my working atmosphere to a friendly and homely atmosphere. That too boosts up my work.

13. What are your weaknesses? I have the tendency to take on too many projects because of my overconfidence in my skills and involve in every problem in deep manner. Apart from these I think I don’t have any specific weakness.

14. What are your carrier goals? I want to be an eminent programmer and I would want to see myself as a prominent person and someone with a good social stature.

15. How would you describe yourself? I describe myself as an enthusiastic, successful person with creativity I will learn things quickly and I can adapt myself to any situation.

16. How would your colleagues describe you? My colleagues describe me as very enthusiastic, hard working and easy going person. They also see me as a trust worthy person and as a helping hand in times of despair.

17. How would your boss describe you?

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My boss actually relates me to his earlier years of his carrier. I guess he would have been very good to improve his stature from an ordinary programmer to boss of an eminent company.

18. What did you most like/dislike about your past job? I liked the job as I learnt to make me ready for new challenges. I learnt to achieve them in a easy way. But there was no space for growth to next level.

19. Describe a situation in your past where you showed initiative? During the recession period I followed new approach to overcome the financial crisis which made the company to overcome that period with no great problems.

20. What were your main responsibilities in your last job? To have a good relationship with client. To have a friendly relationship among colleagues To increase company's turnover.

21. What do you consider your greatest accomplishments? I have achieved an increase in sales by a record 55%. I still hold that record for the highest increase ever achieved.

22. Describe your management style? I have a friendly relationship with my team mates which help to extract more work from them.

23. Do you work better in teams or independently? I have experience in both working as teams and as an individual. But I do my work individually and I consult with my team only when necessary. Well I have found

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a balance between the two and at the day I look up only at how well the work have shaped up and not how I work.

24. How do you work under pressure? Once I had an experience. We were given the wrong deadline for finishing the project. We came to know about the original deadline only four days before and we had completed only 40% of the project. It was very much absorbing and we managed to complete the project with a day to spare. I got a little tensed but held my nerves together in that situation.

25. What other jobs have you applied? I have applied for a couple of jobs, but only the concern I have applied differ not the nature of the job. I have got an offer from Cognizant for the post of program developer.

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2.3. ROLE-PLAY Situation: Ask a stranger for direction from Gandhipuram to Agricultural University. Vignesh : Excuse me. Can you spare me a moment please? Deepak : Ya, go on. Vignesh : I am new to the city and I want to be in Agri University for my paper presentation. Can you give me a direction? Deepak :Ya,sure.Can I know your mode of transport? Vignesh:I have a car. Deepak : Then it is quite easy. First you have drive straight in this road. After a few paces there will be signal. Vignesh: Wait a second,I will note down. Deepak : Ok,take a left turn in the signal, you will be in cross cut road. Vignesh:Pardon. Deepak :Cross cut road... Vignesh:Ok, a strange name. Deepak :Ya.Then you have to go straight through that road without any deviation.At the end you will find an over bridge.You have to drive through that bridge. Vignesh :Excuse me, do you want me to go under or over the bridge? Deepak :You have to go over the bridge.The bridge will deviate into two ways down, one towards Ooty and other towards Poomarket.There will be a sign board,Descend down the bridge toward Poomarket,then you can find the 'Central Theatre' on the left side of the road. There will be a road just opposite to the theatre. Vignesh:I have to drive through that road,Right? Deepak :Ya, but there will be dividers so you will have to take a U turn to drive through that road. Drive along the road for approximately 2 to 2 1/2 km. There will be another signal again go straight within a couple of kilometre you will find the Agri University. Vignesh:Ok,Thank you very much. Deepak :All the best with your paper presentation. Vignesh:Thank you.

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2.4 RESUME WRITING

COVERING LETTER

G.M.Vignesh, 1891-A,Sathy Road, Ganapathy, Coimbatore-06.

10 Mar 2009

To The Manager, Tata Consultancy Services Ltd, Chennai.

Dear Sir, Sub: Application for the post of Software Designer. Ref: Your advertisement in “The Hindu” dated 9 Mar 2009.

This letter is to express my interest in discussing the Software Designer position at Tata Consultancy Services. The opportunity presented is very appealing and I believe that my education and knowledge will make me a competitive candidate for the post.

The key strengths that I possess for success in this position include, but are not limited to, the following:

•

Comprehensive problem solving abilities

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•

Excellent verbal and communication skills

•

Ability to deal with people diplomacy

•

Willingness to learn team facilitator hard work

You will find me to be well efficient, energetic and confident and the type of person whom you may consider as a natural choice for the post.

I can be reached anytime via my mobile number, +91-09944639282. Thank you for your time and consideration. I look forward to speaking with you about this employment opportunity.

Truly, Vignesh.G.M. Enclosed: Resume.

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RESUME

G.M.Vignesh, 1891-A,Sathy Road, Ganapathy, Coimbatore-06. Email : [email protected] Contact no : +91-9944639282

CAREER OBJECTIVE: Seeking a position to utilize my skills and abilities in the Information Technology Industry that offers professional growth while being resourceful, innovative and flexible.

EDUCATION QUALIFICATION: ➢

B.TECH in Information Technology (2001-2005) from Kumaraguru College of Technology with 81% aggregate.

➢

Higher Secondary with 95% aggregate.

SOFTWARE PROFICIENCY: ♦

Languages

:C, C++

♦

DBMS Packages

:Oracle 8i

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♦

Front End

:VB.NET

♦

Operating Systems

:MS DOS,Windows98,NT,2000,XP

♦

Web Designing

: JAVA,HTML,XML

ACHIEVEMENTS: •

Stood First in Inter College Group Discussions. Topic: The affect of cinema on the present generation

•

Participated in Infobattle-2004, a national level event on paper presentation.

•

Participated in college and school level debate and essay competition and received applauds

PROJECT PROFILE: ➢ Built an optimizing compiler for mC++, a C++ subset with support for dynamic object migration over the network between compatible type-spaces. ➢

Built a user-level distributed file system based on NFS with write-through caching, fault tolerance and consistency guarantees..

PERSONAL SKILLS: Comprehensive problem solving abilities, excellent verbal and written communication skills, ability to deal with people diplomatically, willingness to learn team facilitator hard worker.

EXTRA CURRICULAR:

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•

President of English Literature Club in college

•

Secretary of Computer Association in college

•

Event organizer in all school and college annual day functions and other technical events.

PERSONAL PROFILE:

Name

:

G.M.Vignesh

Father’s Name

:

S.Manoharan

Nationality

:

Indian

Date of Birth

:

02 Oct 1986

Marital Status Hobbies Languages Known

DECLARATION

:

Unmarried : :

Reading books, Travelling Tamil, English and Hindi

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I declare that the information furnished above is true to the best of my knowledge.

Place: Coimbatore (G.M.Vignesh)

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2.5. GROUP DISCUSSION Topic

: Should there be private universities?

Members

: Suganya.K.S, Swathithya.K, Thirumala Lakshmi.P.A, Usha Nandhini.P,

Vignesh.G.M, Vimal Raj. Swathithya

: Good morning to one and all present here. Private universities are

educational institutions which are not operated by governments though they may or may not receive funding. Well let us come into the topic “Should there be private universities?” Higher education in India has largely been the preserve of the Government till recently in terms of both funding and provision of education. The Government spending on higher education as a percentage of overall government spending on education is increasing but it is not in par with the increase in demand for higher education. Vignesh

: Yes, the demand for higher education is continuing to increase with more and

more students wanting a higher education today than ever before. How can we bridge the gap between increasing demand and decreasing government funding for higher education? The only option is to tap the private sector to participate in the funding and provision of higher education Suganya

: The task before us now is to come up with ways and means to ensure that

private universities are properly regulated, yet autonomous and independent enough to flourish, and held to high standards to provide quality higher education. If we see the advantages of private universities we can have a comfortable and good exposure of all the things equalizing the government institutions. Vimal

: The first visible advantage is institutional diversity – affording numerous

alternatives for pursuit of advanced education. This diversity varies among higher educational systems. Some private universities have chosen to be relatively small, catering to academic elites. Some aim at specialized training programs, others provide cultural pluralism. Some other emphasizes their differences in styles of instruction. Usha Nandhini

: The diversity of less selective private universities may enhance access to

higher education. The continual adaptation of the changing requirements of external constituencies and knowledge base of higher education connects it to innovation. Thirumala

: The controversial issue within private universities is teaching staff

which is very limited in quantity and quality. Private institutions mainly rely on inviting staff

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from public universities and research universities and research institutions. Although the number of lecturers has been increasing, it has lagged behind the current explosion in number of enrolled students Swathithya

: One more problem is that many lecturers are approaching retirement

age. Those professors are heavily involved in teaching commitment rather than research activities. Private universities make their contributions aiming at fulfilling some indispensable functions ignored by the other institutions such as vocational or in-service programs. Suganya

: They also offer courses in evening or on a week-end basis providing

students are assured to attend and obtain all the compulsory credits required by the universities. Having a part of these functions under private control may assure needed changes and responsiveness, thereby contributing to the diversity and adaptability of the system as a whole. This character is also very important in industrialization trend of the country. Vignesh

: The main goal of many of the private universities is to mint some huge

amount of money. But, some private institutions like to give good education to the students. It’s all like a part of business. Thirumala

: Another major setback is that, although teaching methods are more

flexible, they are still not always consistent with the practical needs of the society. Programs and curricula are excessively theoretical and less responsive to the current industrial needs. Usha Nandhini

: Consequently, students obtain inadequate practical skills after

graduation. Moreover, the universities lack new and modern equipment. Concerning the evaluation issue, there is no fixed standard to evaluate students’ educational quality. Vimal

:But we cannot reject private universities once for all. The Government

should govern boards that actively analyzes the standards of all the universities in regular basis. So as a conclusion we can say that each institution has its own pros and cons but still it lies in our hand to choose the best among them. Thank you.

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2.6. REPORT WRITING CRYPTOGRAPHY AND NETWORK SECURITY

Prepared by: Vignesh.G.M. Approved by: Vidyavathi Ramakrishanan. Prepared for: Communication skills laboratory Date:19.03.2009

TABLE OF CONTENTS:

➢ EXECUTIVE SUMMARY

-

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➢ BACKGROUND

-

43

➢ PROCEDURES

-

43

➢ RESULTS

-

44

➢ DISCUSSION

-

44

➢ CONCLUSION

-

44

➢ RECOMMENDATIONS

-

45

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EXECUTIVE SUMMARY: •

Need for Cryptography.

•

Principles of security

•

Modern cryptography and symmetric encryption

•

Recommendations to prevent damage in spite of adversarial attacks

BACKGROUND: The generic name for the collection of tools designed to protect the data from the hackers is Computer security. Networks security measures are needed to protect the data during transmission. Cryptography refers almost exclusively to encryption. The process of converting ordinary information (plaintext) into unintelligible gibberish (i.e., cipher text) Decryption is the reverse, moving from unintelligible cipher text to plaintext. A cipher (or cypher) is a pair of algorithms which creates the encryption and the reversing decryption. The detailed operation of a cipher is controlled both by the algorithm and, in each instance, by a key. PROCEDURES: All encryption algorithms are based on two general principles: Substitution in which each element in the plain text are mapped into another element. Transposition in which elements in the plain text are rearranged. The fundamental requirement is that no information to be lost. Most systems referred to as product systems involve multiple stages of substitution and transposition. If both the sender and receiver use the same key, the system is referred to as symmetric, single key, secret key or conventional encryption. If the sender and receiver each use a different key, the system is referred to as asymmetric or public key encryption. The plaintext (bit, letter, group of bits or letters)is given as input to the encryption algorithm. The output is the cipher text(coded message)is transmitted to the decryption algorithm to on the receiver side to get the original message.

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Hash function algorithm is applied to a block of data of any size which produces a fixed length output. It makes both hardware and software implementations more practical.

RESULTS:

Cryptography is a method for providing network security. It results in data confidentiality.

Data confidentiality is the protection of transmitted data from passive

attacks. In the context of network security access control is the ability to limit and control the access to host systems and applications via communication links. The goal of cryptanalysis is to find some weakness or insecurity in a cryptographic scheme, thus permitting its subversion or evasion. The purpose of the hash function is to produce a finger print of a file, message or other block of data.

DISCUSSIONS:

The results clearly indicate that cryptography is the important mean to provide security to the data transmitted over the network from sender to the receiver. It is widely used in operating systems like APPLE, MICROSOFT, NOVELL and SUN. It is also used in hardware like cell phones, ATM machines and wireless Ethernet cards.

CONCLUSION:

Thus the cryptography provides way to transfer confidential files and data without being invaded by the hackers. This helps a lot for the government and the military.

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RECOMMENDATIONS: In view of the development of global information and communications networks and the need to ensure concerted solutions, efforts should be made to transfer file or data in the secured manner.