A new perspective on phonetic variation is achieved in this volume
through the construction of a series of 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 units
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 communication.
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