Search results for "Speech corpus"

showing 3 items of 3 documents

Algorithmic Aspects of Speech Recognition: A Synopsis

2000

Speech recognition is an area with a sizable literature, but there is little discussion of the topic within the computer science algorithms community. Since many of the problems arising in speech recognition are well suited for algorithmic studies, we present them in terms familiar to algorithm designers. Such cross fertilization can breed fresh insights from new perspectives. This material is abstracted from A. L. Buchsbaum and R. Giancarlo, Algorithmic Aspects of Speech Recognition: An Introduction, ACM Journal of Experimental Algorithmics, Vol. 2, 1997, http://www.jea.acm.org.

Computer scienceSpeech recognitionSpeech corpusHidden Markov modelGeneralLiterature_REFERENCE(e.g.dictionariesencyclopediasglossaries)
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Towards a Non-Intrusive Context-Aware Speech Quality Model

2020

Understanding how humans judge perceived speech quality while interacting through Voice over Internet Protocol (VoIP) applications in real-time is essential to build a robust and accurate speech quality prediction model. Speech quality is degraded in the presence of background noise reducing the Quality of Experience (QoE). Speech Enhancement (SE) algorithms can improve speech quality in noisy environments. The publicly available NOIZEUS speech corpus contains speech in environmental background noise babble, car, street, and train at two Signal-to-noise ratio (SNRs) 5dB and 10dB. Objective Speech Quality Metrics (OSQM) are used to monitor and measure speech quality for VoIP applications. Th…

Context modelVoice activity detectionNoise measurementComputer scienceSpeech recognitionMean opinion score020206 networking & telecommunicationsSpeech corpus02 engineering and technology01 natural sciencesBackground noiseSpeech enhancement0103 physical sciences0202 electrical engineering electronic engineering information engineeringQuality of experience010301 acoustics2020 31st Irish Signals and Systems Conference (ISSC)
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Linguistic interpretation of speech errors

2016

The paper is an attempt to illustrate the linguistic interpretation of speech, known that it remains insufficiently resolved, especially for Romanian. The cause is given by the multitude of criteria that can or should be considered important in speech processing. The aim of this study is to develope a computational tool in order to identify the possible errors related to the morphosintactic structure of speech. Our goal is to assist users who can receive automatically different suggestions that can help them to improve the quality of their text. Thus, we chose an interdisciplinary approach through speech analysis that brings together the key fields of linguistics, computer science and so on…

Cued speechbusiness.industryComputer scienceRomanianSpeech synthesisSpeech corpusPragmaticscomputer.software_genreSpeech processingIndirect speechlanguage.human_languageLinguisticsCache language modelLanguage technologylanguageArtificial intelligenceComputational linguisticsbusinesscomputerNatural language processing2016 6th International Conference on Computers Communications and Control (ICCCC)
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