TY - JOUR
T1 - Advances in automatic speech recognition by combining information theory and neural network algorithms
AU - Rigoll, Gerhard
PY - 1992/5/20
Y1 - 1992/5/20
N2 - This paper presents some of the newest developments in the field of automatic speech recognition. It concentrates on describing the efforts of combining the two so‐far most successful approaches in automatic speech recognition, namely, information theory and neural network techniques, in order to obtain more improved speech recognition algorithms. An overview of the various approaches to the combination of these two basic technologies is given and the arising problems, such as the choice of the appropriate neural network paradigms, the best possible combination strategies and possibilities for an integrated training of the neural network, and the Markov model parameters, are discussed.
AB - This paper presents some of the newest developments in the field of automatic speech recognition. It concentrates on describing the efforts of combining the two so‐far most successful approaches in automatic speech recognition, namely, information theory and neural network techniques, in order to obtain more improved speech recognition algorithms. An overview of the various approaches to the combination of these two basic technologies is given and the arising problems, such as the choice of the appropriate neural network paradigms, the best possible combination strategies and possibilities for an integrated training of the neural network, and the Markov model parameters, are discussed.
UR - http://www.scopus.com/inward/record.url?scp=84987141329&partnerID=8YFLogxK
U2 - 10.1002/qua.560420414
DO - 10.1002/qua.560420414
M3 - Article
AN - SCOPUS:84987141329
SN - 0020-7608
VL - 42
SP - 741
EP - 750
JO - International Journal of Quantum Chemistry
JF - International Journal of Quantum Chemistry
IS - 4
ER -