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Big Data analytics to assess personality based on voice analysis
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Reconocimiento de voz basado en características DNN Bottleneck
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Implementación y evaluación de un sistema QbE-STD (Query-by-Example Spoken Term Detection)
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An analysis of the influence of deep neural network (DNN) topology in bottleneck feature based language recognition
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ALBAYZIN Query-by-example Spoken Term Detection 2016 evaluation
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An end-to-end approach to language identification in short utterances using convolutional neural networks
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Emulating DNA: Rigorous Quantification of Evidential Weight in Transparent and Testable Forensic Speaker Recognition
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In: IEEE Transactions on Audio, Speech, and Language Processing (2015)
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Emulating DNA: Rigorous Quantification of Evidential Weight in Transparent and Testable Forensic Speaker Recognition
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In: IEEE Transactions on Audio, Speech, and Language Processing (2015)
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Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment
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Acoustic-phonetic decoding of different types of spontaneous speech in Spanish
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Severe apnoea detection using speaker recognition techniques
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Using data-driven and phonetic units for speaker verification
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Multivariate cepstral feature compensation on band-limited data for robust speech recognition
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Acoustic Event Recognition for Low Cost Language Identification
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On the relationship between phonetic modeling precision and phonetic speaker recognition accuracy
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Abstract:
Proceedings of Interspeech-Eurospeech 2005, Lisbon (Portugal) ; Speaker recognition techniques have traditionally relied on purely acoustic features and models. During the last few years, however, the field of speaker recognition has started to show interest in the use of higher level features. In particular, phonetic decodings modeled with statistical language models (n-grams) have already shown its effectiveness in several research works. However, the relationship between phonetic modeling precision and the accuracy of phonetic speaker recognition has not yet been sufficiently analyzed. As part of our preparation for the NIST 2005 speaker recognition evaluation, we have performed a number of experiments that show that there is a negligible correlation between phonetic modeling precision and phonetic speaker recognition accuracy. Furthermore, our experimental results show that phonetic speaker recognition results may even be better when using phonetic decodings in languages different from that of the speech. ; This research was supported by the Spanish Ministry of Science and Technology under project TIC2003-09068- C02-01.
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Keyword:
Informática; speaker recognition
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URL: http://hdl.handle.net/10486/663622
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Inventario de frecuencias fonémicas y silábicas del castellano espontáneo y escrito
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Improved language recognition using better phonetic decoders and fusion with MFCC and SDC features
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Feature analysis for discriminative confidence estimation in spoken term detection
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Assessment of severe apnoea through voice analysis, automatic speech, and speaker recognition techniques
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