Sr. Advisor, Speech Technology and Research Laboratory
Kristin Precoda, Ph.D., is a Sr. Advisor in SRI International’s Speech Technology and Research (STAR) Laboratory.
Publications
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Classification of Lexical Stress Using Spectral and Prosodic Features for Computer-assisted Language Learning Systems
We present a system for detection of lexical stress in English words spoken by English learners. This system was designed to be part of the EduSpeak® computer-assisted language learning (CALL) software.
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Lexical Stress Classification for Language Learning Using Spectral and Segmental Features
We present a system for detecting lexical stress in English words spoken by English learners. The system uses both spectral and segmental features to detect three levels of stress for each syllable in a word.
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Unsupervised topic modeling for leader detection in spoken discourse
In this paper, we describe a method for leader detection in multiparty spoken discourse that relies on unsupervised topic modeling to segment the discourse automatically.
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Detecting Leadership and Cohesion in Spoken Interactions
We present a system for detecting leadership and group cohesion in multiparty dialogs and broadcast conversations in English and Mandarin.
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Detection of agreement and disagreement in broadcast conversations
We present Conditional Random Fields based approaches for detecting agreement/disagreement between speakers in English broadcast conversation shows.
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Automatic identification of speaker role and agreement/disagreement in broadcast conversation
We present supervised approaches for detecting speaker roles and agreement/disagreement between speakers in broadcast conversation shows in three languages: English, Arabic, and Mandarin.