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Acoustic analysis and measurements of distorted speech in the NZ population
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Acoustic analysis and measurements of distorted speech in the NZ population
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Acoustic analysis and measurements of distorted speech in the NZ population
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The 2016 NIST Speaker Recognition Evaluation
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Abstract:
In 2016, the National Institute of Standards and Technology (NIST) conducted the most recent in an ongoing series of speaker recognition evaluations (SRE) to foster research in robust text-independent speaker recognition, as well as measure performance of current state-of-the-art systems. Compared to previous NIST SREs, SRE16 introduced several new aspects including: an entirely online evaluation platform, a fixed training data condition, more variability in test segment duration (uniformly distributed between 10s and 60s), the use of non-English (Cantonese, Cebuano, Mandarin and Tagalog) conversational telephone speech (CTS) collected outside North America, and providing labeled and unlabeled development (a.k.a. validation) sets for system hyperparameter tuning and adaptation. The introduction of the new non-English CTS data made SRE16 more challenging due to domain/channel and language mismatches as compared to previous SREs. A total of 66 research organizations from industry and academia registered for SRE16, out of which 43 teams submitted 121 valid system outputs that produced scores. This paper presents an overview of the evaluation and analysis of system performance over all primary evaluation conditions. Initial results indicate that effective use of the development data was essential for the top performing systems, and that domain/channel, language, and duration mismatch had an adverse impact on system performance.
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Keyword:
AUTOMATED SPEECH RECOGNITION; CTS(conversational telephone speech); NIST(National Institute of Standards and Technology); speaker detection; speaker verification; SRE(speaker recognition evaluation); TECHNOLOGY; test and evaluation; training; Voice Communications
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URL: http://www.dtic.mil/docs/citations/AD1034656
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=AD1034656
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Acoustic analysis and computerized reconstruction of speech in laryngectomised individuals
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Acoustic analysis and computerized reconstruction of speech in laryngectomised individuals
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Acoustic analysis and computerized reconstruction of speech in laryngectomised individuals
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The Voice Conversion Challenge, 2016: multidimensional scaling (MDS) listening test results ...
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Unkn Unknown. - : University of Edinburgh. School of Informatics. Centre for Speech Technology Research, 2016
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Cascading Oscillators in Decoding Speech: Reflection of a Cortical Computation Principle
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Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript)
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The interaction of long-term voice quality with the realisation of focus ; Speech Prosody 2016
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Bionic voice (pilot study) : natural speech restoration for voice impaired individuals
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Bionic voice (pilot study) : natural speech restoration for voice impaired individuals
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Bionic voice (pilot study) : natural speech restoration for voice impaired individuals
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Robust Speech Processing & Recognition: Speaker ID, Language ID, Speech Recognition/Keyword Spotting, Diarization/Co-Channel/Environmental Characterization, Speaker State Assessment
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In: DTIC (2015)
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The Effects of Student Narration in College Engineering Classes
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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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Respirator Speech Intelligibility Testing with an Experienced Speaker
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In: DTIC (2015)
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A Novel Scheme for Speaker Recognition Using a Phonetically-Aware Deep Neural Network
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In: DTIC (2014)
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