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A cross-cultural comparison of educational video quality on college students' anxiety and depression: a cross-sectional content analysis of YouTube and Bilibili. [PDF]
Xu J, He Q, Chen J, Peng X, Liang J.
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Information based speaker verification [PDF]
We discuss the conceptual and computational frameworks of information theory for decision making in speaker verification. The proposed approach departs from other conventional scoring models for speaker verification as the first approach takes into account the quantity of 'surprise' or information content. We compare the new approach with a widely used
Tuan D. Pham, Michael Wagner 0004
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On Deep Speaker Embeddings for Speaker Verification
2021 44th International Conference on Telecommunications and Signal Processing (TSP), 2021In recent years, there has been a tremendous application spike in the field of deep neural networks (DNN), including increasing interest in automatic speaker recognition systems development. Currently, the utilization of DNN-based speaker embeddings, such as x-vectors or d-vectors, is a common way of creating speaker-specific acoustic models. In recent
Maros Jakubec +3 more
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Effective speaker adaptations for speaker verification
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002This paper concerns effective speaker adaptation methods to solve the over-training problem in speaker verification, which frequently occurs when modeling a speaker with sparse training data. While various speaker adaptations have already been applied to speech recognition, these methods have not yet been formally considered in speaker verification ...
Sungjoo Ahn, Sunmee Kang, Hanseok Ko
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Speaker verification: a tutorial
IEEE Communications Magazine, 1990The task of speaker verification, a subset of the general problem of speaker recognition is defined. The feature selection and pattern matching steps of the recognition procedure are examined. Speaker verification system design and performance are discussed, and databases for evaluating them are briefly considered.
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Speaker verification by inexperienced and experienced listeners vs. speaker verification system
2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011This paper describes the participation of the LIA in the Human Assisted Speaker Recognition (HASR) task of the NIST-SRE 2010 evaluation campaign and its extension to a larger number of listeners. The human performance in such unfavorable conditions is analyzed in relation to the decision of a speaker recognition automatic system.
Juliette Kahn +3 more
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Disentangling speaker and channel effects in speaker verification
2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004We show how a joint factor analysis of inter-speaker and intra-speaker variability in a training database which contains multiple recordings for each speaker can be used to construct likelihood ratio statistics for speaker verification which take account of intra-speaker variation and channel variation in a principled way.
Patrick Kenny, Pierre Dumouchel
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