Accent features and idiodictionaries : on improving accuracy for accented speakers in ASR
One of the most widespread approaches to dealing with the problem of accent variation in ASR has been to choose the most appropriate pronunciation dictionary for the speaker from a predefined set of dictionaries. This approach is weak in two ways: firstly that accent types are more numerous and more variable than can be captured in a few dictionaries, even if the knowledge were available to create them and secondly, accents vary in the composition and phonotactics of the phone inventory not just in which phones are used in which word.;In this work, we identify not the speaker's accent, but accent features which allow us to predict by rule their likely pronunciation of all words in the dictionary. Any given speaker is associated with a set of accent features, but it is not a requirement that those features constitute a known accent. We show that by building a pronunciation dictionary for an individual, an idiodictionary, recognition accuracy can be improved over a system using standard accent dictionaries.;The idiodictionary approach could be further enhanced by extending the set of phone models to improve the modelling of phone inventory and variation across accents. However an extended phoneme set is difficult
Tjalve, Michael
Accent features and idiodictionaries : on improving accuracy for accented speakers in ASR. One of the most widespread approaches to dealing with the problem of accent variation in ASR has been to choose the most appropriate pronunciation dictionary for the speaker from a predefined set of dictionaries. This approach is weak in two ways: firstly that accent types are more numerous and more variable than can be captured in a few dictionaries, even if the knowledge were available to create them and secondly, accents vary in the composition and phonotactics of the phone inventory not just in which phones are used in which word.;In this work, we identify not the speaker's accent, but accent features which allow us to predict by rule their likely pronunciation of all words in the dictionary. Any given speaker is associated with a set of accent features, but it is not a requirement that those features constitute a known accent. We show that by building a pronunciation dictionary for an individual, an idiodictionary, recognition accuracy can be improved over a system using standard accent dictionaries.;The idiodictionary approach could be further enhanced by extending the set of phone models to improve the modelling of phone inventory and variation across accents. However an extended phoneme set is difficult
accent feature improve accuracy accent speaker asr widespread approach deal_problem accent variation asr choose appropriate pronunciation dictionary speaker set dictionary weak way_firstly accent_type numerous variable dictionary even knowledge available create secondly accent vary composition phone inventory phone use_word work identify speaker accent accent feature allow predict rule likely pronunciation word dictionary give speaker associate set accent feature requirement feature constitute know accent show building pronunciation dictionary individual recognition accuracy improve system use standard accent dictionary could enhance extend set phone model improve model phone inventory variation across accent however extended phoneme set difficult