Title :
A morphological model for large vocabulary speech recognition
Author :
Elbeze, Marc ; Derouault, Anne-Marie
Author_Institution :
IBM France Sci. Center, Paris, France
Abstract :
A morphological model, applicable to inflected languages, which combines the robustness of the tripos model with the prediction power of the lemma is proposed. A semantic component acts at the lemma level, without taking into account the different inflections of a lemma, thus making its trainable even for 200000 words. The training corpus for the lemma model (consisting of 38 million words) is labeled in terms of lemma and part of speech, using a semiautomatic process. The results obtained with this new model are reported. The model shows another way to put knowledge in the pure probabilistic framework of hidden Markov models
Keywords :
Markov processes; grammars; knowledge engineering; natural languages; speech recognition; hidden Markov models; large vocabulary speech recognition; lemma level; morphological model; natural languages; tripos model; Dictionaries; Hidden Markov models; Natural languages; Predictive models; Robustness; Speech analysis; Speech processing; Speech recognition; Testing; Text recognition; Vocabulary;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on
Conference_Location :
Albuquerque, NM
DOI :
10.1109/ICASSP.1990.115778