Issues in acoustic modeling of speech for automatic speech recognition
Yifan Gong, Jean‐Paul Haton, Jean‐François Mari · 1994
: Stochastic modeling is a flexible method for handling the large variability in speech for recognition applications. In contrast to dynamic time warping where heuristic training methods for estimating word templates are used, stochastic modeling allows a probabilistic and automatic training for estimating models. This paper deals with the improvement of stochastic techniques, especially for a better representation of time varying phenomena. Key-words: Speech recognition, HMM, stochastic trajectory modeling (R'esum'e : tsvp) chapter in the book "Progress and Prospects of Speech Research and Technology", H. Nieman, R. De Mori and G. Hanrieder, editors, INFIX, Sankt Augustin, 1994 Unite de recherche INRIA Lorraine Technopole de Nancy-Brabois, Campus scientifique, 615 rue de Jardin Botanique, BP 101, 54600 VILLERS LE S NANCY (France) Telephone : (33) 83 59 30 30 -- Telecopie : (33) 83 27 83 19 Antenne de Metz, technopole de Metz 2000, 4 rue Marconi, 55070 METZ Telephone : (33) 87 20 35 0...