Computer Programs for Spelling Correction: An Experiment in by J.L. Peterson

By J.L. Peterson

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W3C. (2004a). 0. org/TR/speech-grammar/ W3C. (2004b). 0. org/TR/speech-synthesis/ W3C. (2007). 1. , & Acero, A. (2008). An introduction to voice search. IEEE Signal Processing Magazine, 25(3), 29–38. , & Heeman, P. A. (2010). Initiative conflicts in task-oriented dialogue. Computer Speech and Language, 24, 175–189. 3 Key Concepts in Human Language and Communication As was the case for the preceding chapter on speech technologies, providing a comprehensive description of the various aspects of human language and communication—from the mechanics of speech production to speech comprehension to the social use of language—is beyond the scope of this book, much less this chapter.

This chapter does not cover the details of the necessary data gathering and manipulation. Rather, the focus is on high-level tasks and the operating characteristics of the technologies. Design teams using these technologies either need specialists on the team to perform these tasks or, if available, could purchase the models from vendors. Like FSGs, SLMs fully specify what words they can recognize. Unlike FSGs, users can speak the words in any order. To provide a best guess at what a user said, recognizers use the SLM in combination with language modeling.

Despite its lack of grammaticality (at least, at the sentence level), the first conversation is more natural than the second—more representative of a real-life conversation, and more consistent with the Gricean maxims. In the first conversation, the participants are as informative as required (but not more so), relevant, and brief—in other words, efficient. 5 with a transcript from a recorded interaction. Few of these utterances are grammatical sentences, especially after the caller and agent begin the give-and-take of the questions and answers needed to complete the reservation.

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