During tile past decade, the applicability of hidden Markov models (HMM) to various facets of speech analysi s has been demonstrated in several different experiments. These investigations all rest on the assumption that speech is a quasi-stationary process whose stationary intervals can be identifie
A Markov model acoustic phonetic component for automatic speech recognition †
✍ Scribed by C.C. Tappert
- Publisher
- Elsevier Science
- Year
- 1977
- Weight
- 794 KB
- Volume
- 9
- Category
- Article
- ISSN
- 0020-7373
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✦ Synopsis
A Markov-model acoustic-phonetic component is constructed for the synthesis of standard acoustic representations of connected speech. The primary building blocks are phones with Markov models structured so that phone length, spectral power and fundamental frequency are parametrically controlled. The model generates acoustic parameter outputs at to-ms time steps. The acoustic-phonetic component permits matching between actual acoustic data and internally modeled acoustic data, and can be employed in various ways-to label speech automatically. as a phone decorder to obtain estimated phone strings, and in speech recognizers which match at the acoustic level.
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