CONF stephenson01b/IDIAP Modeling Auxiliary Information in Bayesian Network Based ASR Stephenson, Todd Andrew Magimai-Doss, Mathew Bourlard, Hervé EXTERNAL http://publications.idiap.ch/attachments/papers/2001/todd-eurospeech2001.pdf PUBLIC http://publications.idiap.ch/index.php/publications/showcite/stephenson01a Related documents 7th European Conference on Speech Communication and Technology (Eurospeech~2001) 4 2765-2768 2001 Aalborg, Denmark September 2001 IDIAP-RR 01-11 Automatic speech recognition bases its models on the acoustic features derived from the speech signal. Some have investigated replacing or supplementing these features with information that can not be precisely measured (articulator positions, pitch, gender, etc.) automatically. Consequently, automatic estimations of the desired information would be generated. This data can degrade performance due to its imprecisions. In this paper, we describe a system that treats pitch as an auxiliary information within the framework of Bayesian networks, resulting in improved performance. REPORT stephenson01a/IDIAP Modeling Auxiliary Information in Bayesian Network Based ASR Stephenson, Todd Andrew Magimai-Doss, Mathew Bourlard, Hervé EXTERNAL http://publications.idiap.ch/attachments/reports/2001/rr01-11.pdf PUBLIC Idiap-RR-11-2001 2001 IDIAP In ``7th European Conference on Speech Communication and Technology (Eurospeech~2001)'', 2001 Automatic speech recognition bases its models on the acoustic features derived from the speech signal. Some have investigated replacing or supplementing these features with information that can not be precisely measured (articulator positions, pitch, gender, etc.) automatically. Consequently, automatic estimations of the desired information would be generated. This data can degrade performance due to its imprecisions. In this paper, we describe a system that treats pitch as an auxiliary information within the framework of Bayesian networks, resulting in improved performance.