- Alexander I. Rudnicky. 1987. Using features to empirically generate pronunciation networks. Abstract: The construction of high‐quality lexical models for speech recognition systems is a labor‐intensive process, requiring not only a great deal of time but also appreciable expertise on the part of the human model builder. Techniques that automate all or parts of this process are therefore highly desirable. Two approaches have been used: the generation of pronunciation networks from baseforms by application of phonological rules and the abstraction of such networks from transcription data. This paper describes a semiautomatic procedure for deriving lexical models from manual phonetic transcriptions. The algorithm uses a feature‐based distance metric to align different pronunciations and produces phonetic networks that specify alternate pronunciations for words. The paper describes the results of constructing lexical networks for a 1000‐word vocabulary, using a corpus of 10 000 work tokens. It should be noted that the technique described here is not restricted to manual transcriptions, but can be extended to ...
