考研英語閱讀理解精讀100篇【信息技術(shù)類】

考研英語閱讀理解精讀100篇unit35
Unit 35
Assistants in record shops are used to receiving "humming queries": a customer comes into the store humming a song he wants, but cannot remember either the title or the artist. Knowledgeable staff are often able to name that tune and make a sale. Hummers, though, can be both off-key and off-track. Frequently, therefore, the cash register stays closed and the customer goes away disappointed. A new piece of software may change this. If Online Music Recognition and Searching (OMRAS) is successful, it will be possible to hum a half-remembered tune into a computer and get a match.
 
OMRAS, which has just been unveiled at the International Symposium on Music Information Retrieval, in Paris, is the brainchild of a group of researchers from the Universities of London, Indiana and Massachusetts. Music-recognition programs exist already, of course. Mobile-phone users, for instance, can dial into a system called Shazam, hold their phones to a source of music, and then wait for the title and artist to be texted back to them.
 
Shazam and its cousins work by matching sounds directly to recordings, several million of them, stored in a central database. For Shazam to make a match, though, the music source must be not just similar to, but actually identical with, one of the filed recordings. OMRAS, by contrast, analyses the music. That means it can make a match between different interpretations of the same piece. According to Mark Sandler, the leader of the British side of the project, the program would certainly be able to match performances of the same work by an amateur and a professional pianist. It should also pass the humming-query test.
 
The musical analysis performed by OMRAS is unlike any that a musicologist would recognise. A tune is first digitised, so that it can be processed. It is then subject to such mathematical indignities as wavelet decomposition, multi-resolution Fourier analysis, polyphase filtering and discrete cosine transformation. The upshot is a mathematical model of the sound that contains the essence of the original, without such distractions as style and quality. That essence can then be compared with a library of known essences and a match made. Unlike Shazam, only one library reference per tune is needed.
 
So far, Dr Sandler and his colleagues have been restricted to modelling classical music. Their 3,000-strong database includes compositions by Bach, Beethoven and Mozart. Worries about copyright mean that they have not yet gained access to company archives of pop music, though if the companies realise that the consequence of more humming queries being answered is more sales, this may change. On top of that, OMRAS could help to prevent accidental copyright infringements, in which a composer lifts somebody else's work without realising his inspiration is second-hand. Or, more cynically, it will stop people claiming that any infringement was accidental. There is little point in doing that when a quick check on the Internet could have set your mind at rest that your magnum opus really was yours.
 
注（1）：本文選自Economist；10/19/2002, p77, 2/3p, 1c；
注（2）：本文習(xí)題命題模仿對(duì)象2000年真題text 3第1題（1），2001年真題text 4第2題（2），2004年真題text 3第4題（3）；2003年真題text 1第4題（4），2002年真題text 3第5題（5）；
 
1.       The passage is mainly__________.
 
[A] a comparison of two music-recognition programs
[B] an introduction of a new software
[C] a survey of the music recognition and searching market
[D] an analysis of the functions of music recognition softwares
 
2.       According to the author, one of the distinctive features of OMRAS is________.
 
[A] its ability to analyze music
[B] its large database
[C] its matching speed
[D] its ability to match music of different pieces
 
3.       The word “upshot” (Line 4, Paragraph 4) most probably means_________.
 
[A] last step
[B] final result
[C] goal
[D] program
 
4.       We can learn from the last paragraph that__________.
 
[A] OMRAS will facilitate copyright infringements
[B] OMRAS researchers are fans of classical music
[C] composers can get more inspiration with the help of OMRAS
[D] music companies are yet to realize the value of OMRAS
 
5.       From the text we can see that the writer seems__________.
 
[A] optimistic
[B] uncertain
[C] indifferent
[D] skeptical
 
答案：BABDA
 
篇章剖析
本篇文章是一篇說明文，介紹了一款最新發(fā)布的“聯(lián)機(jī)音樂識(shí)別和查詢系統(tǒng)”。第一段通過一個(gè)生動(dòng)的例子介紹這種系統(tǒng)的功能。第二段和第三段將這種系統(tǒng)和其他的產(chǎn)品的工作原理進(jìn)行了比較。第四段介紹了這種新產(chǎn)品的音樂分析方法。最后一段介紹了有關(guān)音樂版權(quán)問題以及這個(gè)系統(tǒng)在版權(quán)領(lǐng)域所能發(fā)揮的作用。
 
詞匯注釋
query[] n. 詢問
off-key（唱歌）跑調(diào)
off-track 唱錯(cuò)曲子
unveil[] v. 使公諸于眾
symposium[] n. （專家、學(xué)者的）研討會(huì)，專題討論會(huì)，座談會(huì)
retrieval[] n. 檢索；從內(nèi)存或其它存儲(chǔ)設(shè)備中獲取信息的過程
brainchild[] n. 腦力勞動(dòng)成果（指計(jì)劃、發(fā)明等）
text[] v. 以文本形式發(fā)送
musicologist[] n. 音樂學(xué)者
digitize[] v. [計(jì)]將資料數(shù)字化
wavelet[] n. 微[子, 弱, 小]波
decomposition[] n. 分解
multi-resolution  n. 多重分辨率
Fourier analysis  傅立葉分析
polyphase[] adj.多相的
filtering[] n. 過濾, 濾除
discrete[] adj. 離散的
cosine[] n. [數(shù)]余弦
transformation[] n. 變化, 轉(zhuǎn)化
upshot[] n. 結(jié)果
infringement[] n. 侵權(quán)侵害一項(xiàng)權(quán)利或特權(quán)
magnum opus[] n. <拉> 巨著, 杰作, 代表作, 主要作品
 
難句突破
1. Worries about copyright mean that they have not yet gained access to company archives of pop music, though if the companies realise that the consequence of more humming queries being answered is more sales, this may change.
主體句式：worries mean that …
結(jié)構(gòu)分析：這是一個(gè)復(fù)雜句，句中包含一個(gè)that引導(dǎo)的賓語從句，這個(gè)從句中有一個(gè)詞組gain access to，意思是“可以進(jìn)入”，此外，句中還有一個(gè)由though引導(dǎo)的讓步狀語從句，在這個(gè)從句里又有一個(gè)if引導(dǎo)的條件狀語從句，而在這個(gè)條件狀語從句里又有一個(gè)that引導(dǎo)的賓語從句。
句子譯文：對(duì)于版權(quán)的擔(dān)憂意味著他們還無法進(jìn)入各公司的流行音樂資料庫，雖然如果公司意識(shí)到回答更多的哼唱問詢就可以帶來更多銷量的話，這種狀況也許會(huì)有所改變。
2. There is little point in doing that when a quick check on the Internet could have set your mind at rest that your magnum opus really was yours.
主體句式：There is little point…
結(jié)構(gòu)分析：這是一個(gè)復(fù)雜句，句子主體結(jié)構(gòu)是一個(gè)慣用表達(dá)“there is little point in doing something”，意思是“做某事沒有意義”，在這個(gè)句中有一個(gè)when 引導(dǎo)的時(shí)間狀語從句，這個(gè)狀語從句的謂語采用了could have done這種虛擬形式，表示“本來能夠做某事”，另外還有一個(gè)成語動(dòng)詞詞組set one’s mind at rest，意思是“讓某人放心”，rest后面則是由that引導(dǎo)的同位語從句。此外，主體結(jié)構(gòu)中的動(dòng)名詞doing也帶了一個(gè)自己的賓語從句。
句子譯文：如果在互聯(lián)網(wǎng)上快速搜索一下就可以放心地發(fā)現(xiàn)自己的大作的確實(shí)至名歸，那么那種做法也就沒有什么意義了。
 
題目分析
1. 答案為B，屬主旨大意題。一般來說，判斷文章主旨，要看文章第一段，最后一段以及各段的主題句的內(nèi)容。文章第一段作者以一個(gè)音像店顧客通過哼唱方式查詢想要的音樂可能遇到的困難開始，引出話題，一種新的軟件可能改變這一切。接著在下文里，作者介紹了這種軟件的功能，特點(diǎn)，原理，發(fā)展前景等�？v觀全文，這是一篇介紹這種新款軟件的說明文。
2. 答案為A，屬事實(shí)細(xì)節(jié)題。答案見文章第二段第四行。
3. 答案為B，屬猜詞題。文中第4段介紹了OMRAS進(jìn)行音樂分析的過程。用了first，then連接手段。經(jīng)過這兩個(gè)階段后就制成了一個(gè)聲音的數(shù)學(xué)模式�？梢姼鶕�(jù)上下文邏輯，upshot一詞應(yīng)該是“最后的結(jié)果”的意思。
4. 答案為D，屬推理判斷題。文章最后一段提到由于擔(dān)心版權(quán)問題，OMRAS的研究人員尚且無法訪問公司的流行音樂庫。但是，“如果公司意識(shí)到回答更多的哼唱問詢就可以帶來更多銷量的話，這種狀況也許會(huì)有所改變”。由此可見，音樂公司還沒有意識(shí)到這款軟件的價(jià)值。
5. 答案為A，屬推理判斷題。根據(jù)上文，作者介紹了OMRAS的相比其他產(chǎn)品的優(yōu)越性能，繼而提到它在防止侵權(quán)方面所能起到的作用。最后說，人們只需在互聯(lián)網(wǎng)上快速搜索一下就可以放心地發(fā)現(xiàn)自己的大作并沒有抄襲別人作品的痕跡�？梢�，作者對(duì)于這種新產(chǎn)持積極樂觀的態(tài)度。
 
參考譯文
音像店的店員已經(jīng)習(xí)慣了接受“哼唱問詢”：一位顧客走進(jìn)店來，把他想要，卻又記不起名稱或者歌手的那首歌哼唱出來。熟悉音樂的店員一般都能說出曲調(diào)的名稱，做成一筆交易。不過，那些哼唱音樂的人很可能不但跑調(diào)而且還搞錯(cuò)了曲子。因此，很多時(shí)候收銀機(jī)都是關(guān)著的，顧客也只能失望地離去。一款新軟件也許會(huì)改變這種狀況。如果“聯(lián)機(jī)音樂識(shí)別和查詢系統(tǒng)”（OMRAS）取得成功的話，那么把記得不太清楚的曲調(diào)對(duì)著電腦哼唱一遍也許就能找出匹配的音樂。
 
最近剛在巴黎舉行的“音樂信息檢索國際會(huì)議”上被公布的OMRAS是來自倫敦，印第安納和馬薩諸塞等地的大學(xué)研究人員的智慧結(jié)晶。當(dāng)然，音樂識(shí)別軟件早就問世了。舉例來說，手機(jī)用戶可以撥打一個(gè)叫做“快變”（Shazam）的系統(tǒng)，用手機(jī)話筒對(duì)準(zhǔn)一個(gè)音樂源，然后等待樂曲的名稱和演奏/唱者等信息以文本形式發(fā)送到他們的手機(jī)上。
 
“快變”及其類似產(chǎn)品的工作原理都是將聲音和幾百萬首儲(chǔ)存在一個(gè)中央數(shù)據(jù)庫中的錄音資料加以匹配。不過，要讓“快變”匹配成功，音樂源不僅要和已歸檔的錄音相似，而且還必須一致才行。與之相比，OMRAS則對(duì)音樂進(jìn)行分析。這就意味著它可以在同一歌曲的不用演繹風(fēng)格之間進(jìn)行匹配。該項(xiàng)目英國小組的負(fù)責(zé)人馬克•桑德勒說，這一系統(tǒng)當(dāng)然能夠?qū)�業(yè)余鋼琴演奏者和職業(yè)鋼琴家演奏的同一作品匹配出來。它也應(yīng)該通過“哼唱問詢”測(cè)試。
 
OMRAS的音樂分析方法不同于音樂學(xué)者了解的任何方法。一個(gè)樂曲先是被數(shù)字化，這樣就可以對(duì)它進(jìn)行處理了。接下來它還要經(jīng)過一些數(shù)學(xué)處理程序，比如小波分解，多重分辨率傅立葉分析，多相過濾，離散余弦變換等。最終得出一個(gè)聲音的數(shù)學(xué)模式，它包含了原始聲音的要素，并排除了風(fēng)格，質(zhì)量等干擾因素。接下來就可以把這種聲音要素和聲音庫中已知的各種聲音要素加以比對(duì)并進(jìn)行匹配。不同于“快變”的是，每一個(gè)曲調(diào)只需要一個(gè)聲音庫參考要素。
 
目前，桑德勒博士和他的同事們一直被限制在制作古典音樂模式的范圍內(nèi)。他們的數(shù)據(jù)庫里有包括巴赫，貝多芬和莫扎特的作品在內(nèi)的三千多首樂曲。對(duì)于版權(quán)的擔(dān)憂意味著他們還無法進(jìn)入各公司的流行音樂資料庫，雖然如果公司意識(shí)到回答更多的哼唱問詢就可以帶來更多銷量的話，這種狀況也許會(huì)有所改變。除此之外，OMRAS還能夠幫助防止不經(jīng)意發(fā)生的侵犯版權(quán)行為，例如一個(gè)作曲家誤把別人的作品當(dāng)作自己的靈感而出現(xiàn)的剽竊行為。更具嘲諷意味的是，它甚至還可以防止人們宣稱自己的侵權(quán)行為是無心之錯(cuò)。如果在互聯(lián)網(wǎng)上快速搜索一下就可以放心地發(fā)現(xiàn)自己的大作的確實(shí)至名歸，那么那種做法也就沒有什么意義了。

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