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Machine Recognition vs Human Recognition of Voices
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In: DTIC (2012)
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Speaker Clustering for a Mixture of Singing and Reading (Preprint)
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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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Segregation of Whispered Speech Interleaved with Noise or Speech Maskers
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In: DTIC (2011)
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The SRI NIST 2010 Speaker Recognition Evaluation System (PREPRINT)
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In: DTIC (2011)
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Recovering Asynchronous Watermark Tones from Speech
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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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Long Term Examination of Intra-Session and Inter-Session Speaker Variability
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In: DTIC (2009)
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Perturbation and Pitch Normalization as Enhancements to Speaker Recognition
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In: DTIC (2009)
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Long Term Examination of Intra-Session and Inter-Session Speaker Variability
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In: DTIC (2009)
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Automating Convoy Training Assessment to Improve Soldier Performance
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In: DTIC (2008)
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Odds of Successful Transfer of Low-level Concepts: A Key Metric for Bidirectional Speech-to-Speech Machine Translation in DARPA's TRANSTAC Program
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In: DTIC (2008)
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Abstract:
The Spoken Language Communication and Translation System for Tactical Use (TRANSTAC) program is a Defense Advanced Research Agency (DARPA) program to create bidirectional speech-to-speech machine translation (MT) that will allow U.S. Soldiers and Marines, speaking only English, to communicate, in tactical situations, with civilian populations who speak only other languages (for example, Iraqi Arabic). A key metric for the program is the odds of successfully transferring low-level concepts, defined as the source-language content words. The National Institute of Standards and Technology (NIST) has now carried out two large-scale evaluations of TRANSTAC systems, using that metric. In this paper we discuss the merits of that metric. It has proven to be quite informative. We describe exactly how we defined this metric and how we obtained values for it from panels of bilingual judges--allowing others to do what we have done. We compare results on this metric to results on Likert-type judgments of semantic adequacy, from the same panels of bilingual judges, as well as to a suite of typical automated MT metrics (BLEU, TER, METEOR). ; Presented at the International Conference Language Resources and Evaluation (LREC) (6th) held in Marrakech, Morocco on 28-30 May 2008. Published in the Proceedings of the International Conference Language Resources and Evaluation (LREC) (6th), 2008. The original document contains color images.
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Keyword:
*MACHINE TRANSLATION; *SEMANTIC ADEQUACY; *SPEECH; *SPEECH TO SPEECH TRANSLATION; CONTENT WORDS; Linguistics; METRICS; SEMANTICS; SOURCE LANGUAGE; SYMPOSIA; TARGET LANGUAGE; Voice Communications; WORDS(LANGUAGE)
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA519222 http://www.dtic.mil/docs/citations/ADA519222
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14 |
Iterated Class-Specific Subspaces for Speaker-Dependent Phoneme Classification
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In: DTIC (2008)
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Listener Detection of Talker Stress in Low-Rate Coded Speech
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In: DTIC (2008)
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Comparing Evaluation Metrics for Sentence Boundary Detection
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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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A Methodology to Predict Specific Communication Themes from Overall Communication Volume for Individuals and Teams
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In: DTIC (2006)
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Toward an Interagency Language Roundtable Based Assessment of Speech-to-Speech Translation Capabilities
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In: DTIC (2006)
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The Mixer and Transcript Reading Corpora: Resources for Multilingual, Crosschannel Speaker Recognition Research
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In: DTIC (2006)
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