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Unformatted text preview: D R A F T Speech and Language Processing: An introduction to natural language processing, computational linguistics, and speech recognition. Daniel Jurafsky & James H. Martin. Copyright c circlecopyrt 2007, All rights reserved. Draft of July 25, 2007. Do not cite without permission. 9 AUTOMATIC SPEECH RECOGNITION When Frederic was a little lad he proved so brave and daring, His father thought he’d ’prentice him to some career seafaring. I was, alas! his nurs’rymaid, and so it fell to my lot To take and bind the promising boy apprentice to a pilot — A life not bad for a hardy lad, though surely not a high lot, Though I’m a nurse, you might do worse than make your boy a pilot. I was a stupid nurs’rymaid, on breakers always steering, And I did not catch the word aright, through being hard of hearing; Mistaking my instructions, which within my brain did gyrate, I took and bound this promising boy apprentice to a pirate. The Pirates of Penzance , Gilbert and Sullivan, 1877 Alas, this mistake by nurserymaid Ruth led to Frederic’s long indenture as a pirate and, due to a slight complication involving 21st birthdays and leap years, nearly led to 63 extra years of apprenticeship. The mistake was quite natural, in a Gilbert-and-Sullivan sort of way; as Ruth later noted, “The two words were so much alike!” True, true; spoken language understanding is a difficult task, and it is remarkable that humans do as well at it as we do. The goal of automatic speech recognition ( ASR ) research is to ASR address this problem computationally by building systems that map from an acoustic signal to a string of words. Automatic speech understanding ( ASU ) extends this goal to producing some sort of understanding of the sentence, rather than just the words. The general problem of automatic transcription of speech by any speaker in any en- vironment is still far from solved. But recent years have seen ASR technology mature to the point where it is viable in certain limited domains. One major application area is in human-computer interaction. While many tasks are better solved with visual or pointing interfaces, speech has the potential to be a better interface than the keyboard for tasks where full natural language communication is useful, or for which keyboards are not appropriate. This includes hands-busy or eyes-busy applications, such as where the user has objects to manipulate or equipment to control. Another important ap- plication area is telephony, where speech recognition is already used for example in spoken dialogue systems for entering digits, recognizing “yes” to accept collect calls, finding out airplane or train information, and call-routing (“Accounting, please”, “Prof....
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- Fall '11
- Natural Language Processing, Speech recognition, RA FT