| Title |
Speech Understanding and Speech Translation in Various Domains by Maximum a-posteriori Semantic Decoding |
| Authors |
Johannes Müller, Holger Stahl |
| Abstract |
This paper describes a domain-limited system for speech understanding as
well as for speech translation. An integrated semantic decoder directly converts
the preprocessed speech signal into its semantic representation by a maximum
a-posteriori classification. With the combination of probabilistic knowledge on
acoustic, phonetic, syntactic, and semantic levels, the semantic decoder extracts
the most probable meaning of the utterance. Any separate speech recognition stage
is not needed because of the integration of the Viterbi-algorithm (calculating
acoustic probabilities by the use of Hidden-Markov-Models) and a probabilistic
chart parser (calculating semantic and syntactic probabilities by especial
models). The semantic structure is introduced as representation of an utterance's
meaning. It can be used as intermediate level for a succeeding intention decoder
(within a speech understanding system for the control of a running application
by spoken inputs) as well as interlingua-level for a succeeding language
production unit (within an automatic speech translation system for the creation
of spoken output in another language). Following the above principles and using
the respective algorithms, speech understanding and speech translation front-ends
for the domains 'graphic editor', 'service robot', 'medical image visualization'
and 'scheduling dialogues' could be successfully realized. |
| Reference |
Proceedings "International Symposium on Engineering of Intelligent Systems"
EIS 98 (La Laguna, Spain, 1998), vol. 2 "Neural Networks", pp. 256-267 |
| Year |
1998 |
| Language |
English |
| Full Paper |
 download pdf file |
Kontakt