Title :
Pronunciation modelling for conversational speech recognition: a status report from WS97
Author :
Byrne, B. ; Finke, M. ; Khudanpur, S. ; McDonough, J. ; Nock, H. ; Riley, M. ; Saraclar, M. ; Wooters, C. ; Zavaliagkos, G.
Author_Institution :
Center for Language & Speech Process., Johns Hopkins Univ., Baltimore, MD, USA
Abstract :
Accurately modelling of pronunciation variability in conversational speech is an important component for automatic speech recognition. We describe some of the projects undertaken in this direction at WS97 [the Fifth LVCSR (large-vocabulary conversational speech recognition) Summer Workshop], held at Johns Hopkins University, Baltimore, in July-August 1997. We first illustrate a use of hand-labelled phonetic transcriptions of a portion of the Switchboard corpus, in conjunction with statistical techniques, to learn alternatives to canonical pronunciations of words. We then describe the use of these alternative pronunciations in a recognition experiment as well as in the acoustic training of an automatic speech recognition system. Our results show a reduction of the word error rate in both cases-0.9% without acoustic retraining and 2.2% with acoustic retraining
Keywords :
learning (artificial intelligence); speech recognition; statistics; vocabulary; Switchboard corpus; acoustic retraining; acoustic training; automatic speech recognition system; canonical pronunciations; hand-labelled phonetic transcriptions; large-vocabulary conversational speech recognition; learning; pronunciation modelling; pronunciation variability; statistical techniques; word error rate; Automatic speech recognition; Decision trees; Dictionaries; Error analysis; Natural languages; Robustness; Speech processing; Speech recognition; Vegetation mapping; Vocabulary;
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.1997.658973
