Two Approaches to Class-Based Language Models for ASR

In this work, we propose and formulate two different approaches for the language model employed in an Automatic Speech Recognition application. Both approaches make use of class-based language models, but taking into account that the classes are made up of segments or sequences of words. Experiments, carried out over a spontaneous dialogue corpus in Spanish, demonstrate the ability of the proposed models to learn the way in which the language is generated.

[1]  Thomas Niesler,et al.  A variable-length category-based n-gram language model , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[2]  Enrique Vidal,et al.  Inference of k-Testable Languages in the Strict Sense and Application to Syntactic Pattern Recognition , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Thomas Niesler,et al.  Comparison of part-of-speech and automatically derived category-based language models for speech recognition , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).

[4]  Isabel Trancoso,et al.  Transducer composition for "on-the-fly" lexicon and language model integration , 2001, IEEE Workshop on Automatic Speech Recognition and Understanding, 2001. ASRU '01..

[5]  Hong-Kwang Jeff Kuo,et al.  Phrase-based language models for speech recognition , 1999, EUROSPEECH.

[6]  Hermann Ney,et al.  Improvements in Phrase-Based Statistical Machine Translation , 2004, NAACL.

[7]  Frederick Jelinek,et al.  Statistical methods for speech recognition , 1997 .

[8]  M. Inés Torres,et al.  Category-based Language Models in a Spanish Spoken Dialogue System , 2006, Proces. del Leng. Natural.

[9]  Franz Josef Och,et al.  An Efficient Method for Determining Bilingual Word Classes , 1999, EACL.

[10]  Frédéric Bimbot,et al.  Language modeling by variable length sequences: theoretical formulation and evaluation of multigrams , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[11]  M. Inés Torres,et al.  k-TSS language models in speech recognition systems , 2001, Comput. Speech Lang..

[12]  Eduardo Lleida,et al.  Design and acquisition of a telephone spontaneous speech dialogue corpus in Spanish: DIHANA , 2006, LREC.

[13]  Alexander H. Waibel,et al.  Class phrase models for language modeling , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[14]  Daniel Marcu,et al.  A Phrase-Based,Joint Probability Model for Statistical Machine Translation , 2002, EMNLP.

[15]  Joan-Andreu Sánchez,et al.  Estimation of stochastic context-free grammars and their use as language models , 2005, Comput. Speech Lang..

[16]  M. Lennig,et al.  A language model for very large-vocabulary speech recognition , 1992 .

[17]  Imed Zitouni,et al.  Backoff hierarchical class n-gram language models: effectiveness to model unseen events in speech recognition , 2007, Comput. Speech Lang..