Speech Recognition via Phonetically Featured Syllables

Simon King, Todd Stephenson, Stephen Isard, Paul Taylor, Alex Strachan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

We describe a speech recogniser which uses a speech production-motivated phonetic-feature description of speech. We argue that this is a natural way to describe the speech signal and offers an efficient intermediate parameterisation for use in speech recognition. We also propose to model this description at the syllable rather than phone level. The ultimate goal of this work is to generate syllable models whose parameters explicitly describe the trajectories of the phonetic features of the syllable. We hope to move away from Hidden Markov Models (HMMs) of context-dependent phone units. As a step towards this, we present a preliminary system which consists of two parts: recognition of the phonetic features from the speech signal using a neural network; and decoding of the feature-based description into phonemes using HMMs.
Original languageEnglish
Title of host publicationICSLP `98
Subtitle of host publication5th International Conference on Spoken Language Processing
PublisherInternational Speech Communication Association
Number of pages4
ISBN (Print)ISSN: 1990-9772
Publication statusPublished - 1 Dec 1998


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