Mapping context dependent acoustic information into context independent form by LVQ (1994)
| Citations: | 4 - 2 self |
BibTeX
@MISC{Mäntysalo94mappingcontext,
author = {Jyri Mäntysalo and Kari Torkkola and Teuvo Kohonen and Kari Torkkola},
title = {Mapping context dependent acoustic information into context independent form by LVQ},
year = {1994}
}
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Abstract
In the framework of phonemic speech recognition using Hidden Markov Models (HMMs) together with codebooks trained by Learning Vector Quantization (LVQ), a novel way to model context-dependencies in speech is presented. We use LVQ to map acoustic contextual data into context-independent phonemic form. The acoustic data is in the form of concatenated averages of successive short-time feature vectors. This mapping eliminates the need to employ context dependent phonemic, for example, triphone HMMs, and the difficulties associated therein. Instead, simpler context-independent discrete observation HMMs suffice. We report excellent results for a speaker dependent task for Finnish. Zusammenfassung Wir diskutieren ein neues Modell von Kontextabhangigkeiten in der phonemischen Spracherkennung. Unser Modell basiert auf den Methoden der Hidden-Markov-Modelle (HMM) und der lernende Vektorquantisierung (LVQ). Wir benutzen LVQ, um Informationen uber den akustischen Kontext in eine kontextunabhang...
