A new perspective on phonetic variation is achieved in this volume through the construction of a series of computational models of spoken American English. In the past, computer theorists and programmers investigating pronunciation have often relied on their own knowledge of the language or on limited transcription data. Speech recognition researchers, on the other hand, have drawn on a great deal of data but without examining in detail the information about pronunciation the data contains. The authors combine the best of each approach to develop probabilistic and rule-based computational models of transcription data.
An ongoing controversy in studies of phonetic variation is the existence and proper definition of a phonetic unit. The authors argue that assumptions about the unit s of spoken language are critical to a computational model. Their computational models employ suprasegmental elements such as syllable boundaries, stress, and position in a unit called a metrical foot. The use of such elements in modeling data enables the creation of better computational models for both recognition and synthesis technology. This book should be of interest to speech engineers, linguists, and anyone who wishes to understand symbolic systems of communications.
and are both researchers at Xerox Palo Alto Research Center, working in the area of language and machine perception.
- 1 The enterprise of modeling the sound of a word
- 2 Hand-transcribed American English speech
- 3 Predicting possible pronounciations
- 4 Word confusion, sound stability
- 5 Statistical modeling of phonological variation
- 6 Final remarks
- A Coverage of the PPS
- B Cohorts produced by PPS