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Non-Parametric Bayesian Subspace Models for Acoustic Unit Discovery
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In: https://hal.archives-ouvertes.fr/hal-03467205 ; 2021 (2021)
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Speaker embeddings by modeling channel-wise correlations ...
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Abstract:
Speaker embeddings extracted with deep 2D convolutional neural networks are typically modeled as projections of first and second order statistics of channel-frequency pairs onto a linear layer, using either average or attentive pooling along the time axis. In this paper we examine an alternative pooling method, where pairwise correlations between channels for given frequencies are used as statistics. The method is inspired by style-transfer methods in computer vision, where the style of an image, modeled by the matrix of channel-wise correlations, is transferred to another image, in order to produce a new image having the style of the first and the content of the second. By drawing analogies between image style and speaker characteristics, and between image content and phonetic sequence, we explore the use of such channel-wise correlations features to train a ResNet architecture in an end-to-end fashion. Our experiments on VoxCeleb demonstrate the effectiveness of the proposed pooling method in speaker ... : Accepted at Interspeech 2021 ...
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Keyword:
Audio and Speech Processing eess.AS; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering
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URL: https://dx.doi.org/10.48550/arxiv.2104.02571
https://arxiv.org/abs/2104.02571
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Bayesian multilingual topic model for zero-shot cross-lingual topic identification ...
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A Hierarchical Subspace Model for Language-Attuned Acoustic Unit Discovery ...
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AUTOMATIC LEARNING OF A PHONOLOGICAL SYSTEM: A CASE STUDY ON MBOSHI
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In: International Conference Language Technologies for All (LT4ALL) ; https://hal.archives-ouvertes.fr/hal-03478242 ; International Conference Language Technologies for All (LT4ALL), 2019, Paris, France (2019)
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Short-duration Speaker Verification (SdSV) Challenge 2021: the Challenge Evaluation Plan ...
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Bayesian models for unit discovery on a very low resource language
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In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ; https://hal.archives-ouvertes.fr/hal-01709589 ; IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Apr 2018, Calgary, Alberta, Canada (2018)
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An Empirical Evaluation of Zero Resource Acoustic Unit Discovery ...
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Approaches to automatic lexicon learning with limited training examples
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In: http://infoscience.epfl.ch/record/203451 (2014)
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Subspace Gaussian Mixture Models for speech recognition
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In: http://infoscience.epfl.ch/record/203448 (2014)
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Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models
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In: http://infoscience.epfl.ch/record/203450 (2014)
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The Kaldi Speech Recognition Toolkit
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In: http://infoscience.epfl.ch/record/192584 (2013)
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The Kaldi Speech Recognition Toolkit
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In: http://infoscience.epfl.ch/record/192761 (2013)
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| 17 |
Improving the Capacity of Language Recognition Systems to Handle Rare Languages Using Radio Broadcast Data
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In: DTIC (2011)
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