Search results for: “stolcke”
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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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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 downstream language processing modules.
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The ICSI-SRI-UW Metadata Extraction System
We describe a state-of-the-art system for automatic detection of “metadata” in both broadcast news and spontaneous telephone conversations, developed as part of the DARPA EARS Rich Transcription program.
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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 of three aspects of this effort.
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From Switchboard to Meetings: Development of the 2004 ICSI-SRI-UW Meeting Recognition System
We describe the ICSI-SRI-UW team’s entry in the Spring 2004 NIST Meeting Recognition Evaluation. The system was derived from SRI’s 5xRT Conversational Telephone Speech (CTS) recognizer by adapting CTS acoustic and language models to the Meeting domain.
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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.
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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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Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech
We compare and contrast two different models for detecting sentence-like units in continuous speech. Both models combine lexical, syntactic, and prosodic information.
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Modeling NERFs for Speaker Recognition
We introduce a new type of feature to capture long-range patterns associated with individual speakers or with speaking styles. NERFs, or Nonuniform Extraction Region Features, are defined based on regions of speech that are delimited by various automatically extractable events of interest. We propose three methods for modeling NERFs that cope with missing features.
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Voicing Feature Integration in SRI’s Decipher LVCSR System
We augment the Mel cepstral (MFCC) feature representation with voicing features from an independent front end.
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The Use of a Linguistically Motivated Language Model in Conversational Speech Recognition
In this paper we show that such a model can be used effectively and efficiently in all stages of a complex, multi-pass conversational telephone speech recognition system.
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TRAPping Conversational Speech: Extending TRAP/Tandem Approaches to Conversational Telephone Speech Recognition
In this paper we report experiments with a reduced conversational speech task that led to the adoption of a number of engineering decisions for the design of an acoustic front end. We then describe our results with this front end on a full vocabulary conversational telephone speech task. In both cases the front end yielded…