Publications
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Modeling Prosodic Feature Sequences for Speaker Recognition
We describe a novel approach to modeling idiosyncratic prosodic behavior for automatic speaker recognition.
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Scaling Up Technology-Based Educational Innovations
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Angler: Collaboratively Expanding your Cognitive Horizon
The tool helps the group through the process of forming consensus, while preserving and quantifying differing ways of thinking. Angler provides a Web-based collaborative environment that allows users distributed by…
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Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov model
We introduce the Switching Hidden Semi-Markov Model (S-HSMM), a two-layered extension of the hidden semi-Markov model (HSMM) for the modeling task.
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Liquid-phase deposition of single-phase alpha-copper-indiumdiselenide,
Based on the first complete CuInSe phase diagram, which was recently established, we propose a new method for making single-phase copper-indium-diselenide (CuInSe2) films for high-specific-power photovoltaic applications: liquid-phase deposition.
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A Wizard of Oz framework for collecting spoken human-computer dialogs
This paper describes a data collection process aimed at gathering human-computer dialogs in high-stress or “busy” domains where the user is concentrating on tasks other than the conversation, for example,…
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SVM Modeling of “SNERF-Grams” for Speaker Recognition
We describe a new approach to modeling idiosyncratic prosodic behavior for automatic speaker recognition. The approach computes prosodic features by syllable, and models the syllable-feature sequences using support vector machines…
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Effective Acoustic Modeling for Rate-of-Speech Variation in Large Vocabulary Conversational Speech Recognition
We investigate several variants of speech-rate-dependent acoustic models for large-vocabulary conversational speech recognition, in the framework of combining rate-specific models in decoding to compensate for speech rate variation.
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National Early Intervention Longitudinal Study (NEILS): Family Outcomes at the End of Early Intervention
The report has two primary aims: to describe the outcomes reported by families following their experience with early intervention programs, and to identify a subset of families who were less…
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On Using MLP Features in LVCSR
One of the major research thrusts in the speech group at ICSI is to use Multi-Layer Perceptron (MLP) based features in automatic speech recognition (ASR). This paper presents a study…
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Using Machine Learning to Cope with Imbalanced Classes in Natural Speech: Evidence from Sentence Boundary and Disfluency Detection
We investigate machine learning techniques for coping with highly skewed class distributions in two spontaneous speech processing tasks. Both tasks, sentence boundary and disfluency detection, provide important structural information for…
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Morphology-Based Language Modeling for Arabic Speech Recognition
In this paper we investigate the use of morphology-based language models at different stages in a speech recognition system for conversational Arabic.