Title :
Language modeling for robust balancing of acoustic and linguistic probabilities
Author :
Ogawa, A. ; Takeda, Kenji ; Itakura, F.
Author_Institution :
Dept. of Inf. Electron., Nagoya Univ., Japan
Abstract :
The length of a word sequence is not taken into account under language modeling in n-gram local probability modeling. Due to this property, the optimal value of the language weight for balancing acoustic and linguistic probabilities is affected by the sequence length. To deal with this problem, a new language model is developed based on the Bernoulli trial model. By taking the sequence length into account, not only is better recognition accuracy achieved, but also more robust balancing with the acoustic probability, as compared with the normal n-gram model
Keywords :
acoustic signal processing; linguistics; modelling; natural languages; probability; sequences; speech recognition; Bernoulli trial model; acoustic probability; language modeling; language weight optimal value; linguistic probability; n-gram local probability modeling; n-gram model; robust balancing; speech recognition accuracy; word sequence length; Robustness;
Conference_Titel :
Automatic Speech Recognition and Understanding, 1997. Proceedings., 1997 IEEE Workshop on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-7803-3698-4
DOI :
10.1109/ASRU.1997.659012