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Study of Discussion Record Analysis Using Temporal Data Crystallization and Its Application to TV Scene Analysis
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In: DTIC (2015)
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Computational Modeling of Emotions and Affect in Social-Cultural Interaction
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In: DTIC (2013)
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A Submodularity Framework for Data Subset Selection
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In: DTIC (2013)
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Speech Synthesis Using Perceptually Motivated Features
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In: DTIC (2012)
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Machine Recognition vs Human Recognition of Voices
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In: DTIC (2012)
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Compressed Domain Automatic Level Control Based on ITU-T G.722.2
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In: DTIC (2012)
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USSS-MITLL 2010 Human Assisted Speaker Recognition
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In: DTIC (2010)
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Multitalker Speech Perception with Ideal Time-Frequency Segregation: Effects of Voice Characteristics and Number of Talkers
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In: DTIC (2009)
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Pictures from Words, Pictures from Text: Constructing Pictorial Representations of Meaning from Text
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In: DTIC (2009)
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The Multi-Session Audio Research Project (MARP) Corpus: Goals, Design and Initial Findings
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In: DTIC (2009)
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Iterated Class-Specific Subspaces for Speaker-Dependent Phoneme Classification
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In: DTIC (2008)
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Multimodal Meeting Capture and Understanding with the CALO Meeting Assistant
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In: DTIC (2007)
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Error Awareness and Recovery in Conversational Spoken Language Interfaces
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In: DTIC (2007)
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Using Prosody for Automatic Sentence Segmentation of Multi-Party Meetings
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In: DTIC (2006)
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Abstract:
We explore the use of prosodic features beyond pauses, including duration, pitch, and energy features, for automatic sentence segmentation of ICSI meeting data. We examine two different approaches to boundary classification: score-level combination of independent language and prosodic models using HMMs, and feature-level combination of models using a boosting-based method (BoosTexter). We report classification results for reference word transcripts as well as for transcripts from a state-of-the-art automatic speech recognizer (ASR). We also compare results using the lexical model plus a pause-only prosody model, versus results using additional prosodic features. Results show that (1) information from pauses is important, including pause duration both at the boundary and at the previous and following word boundaries; (2) adding duration, pitch, and energy features yields significant improvement over pause alone; (3) the integrated boosting-based model performs better than the HMM for ASR conditions; (4) training the boosting-based model on recognized words yields further improvement. ; Presented at the International Conference on Text, Speech, and Dialogue (9th) (TSD 2006) held in Brno, Czech Republic on 11-15 Sep 2006. Published in the Proceedings of the International Conference on Text, Speech, and Dialogue (9th), 2006. Sponsored in part by National Science Foundation contract no. IIS-0121396.
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Keyword:
*BOUNDARIES; *MODELS; *PROSODIC FEATURES; *PROSODY; *SENTENCE SEGMENTATION; *SPEECH RECOGNITION; ALGORITHMS; ASR(AUTOMATIC SPEECH RECOGNIZER); AUTOMATIC; BOOSTING; CLASSIFICATION; CLASSIFIERS; Cybernetics; HMM(HIDDEN MARKOV MODELS); LEXICAL FEATURES; Linguistics; MARKOV PROCESSES; PAUSES; SYMPOSIA; TEAMS(PERSONNEL); Voice Communications; WORDS(LANGUAGE)
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URL: http://www.dtic.mil/docs/citations/ADA459015 http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA459015
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Investigation on Mandarin Broadcast News Speech Recognition
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In: DTIC (2006)
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Objective Measurement of the Speech Transmission Quality of Vocoders by Means of the Speech Transmission Index
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In: DTIC (2005)
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Cognitive Tools for Humanoid Robots in Space
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In: DTIC AND NTIS (2004)
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Towards a Warfighter's Associate: Eliminating the Operator Control Unit
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In: DTIC (2004)
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