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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 10 of 10 1 BUT Opensat 2019 Speech Recognition System ... Karafiát, Martin; Baskar, Murali Karthick; Szöke, Igor. - : arXiv, 2020 BASE Show details 2 Analysis of Multilingual Sequence-to-Sequence speech recognition systems ... Karafiát, Martin; Baskar, Murali Karthick; Watanabe, Shinji. - : arXiv, 2018 BASE Show details 3 Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling ... Cho, Jaejin; Baskar, Murali Karthick; Li, Ruizhi. - : arXiv, 2018 BASE Show details 4 Study of Large Data Resources for Multilingual Training and System Porting (Pub Version, Open Access) Grezl, Frantisek; Egorova,Ekaterina; Karafiat,Martin. - 2016 BASE Show details 5 Approaches to automatic lexicon learning with limited training examples Goel, Nagendra; Thomas, Samuel; Agarwal, Mohit... In: http://infoscience.epfl.ch/record/203451 (2014) BASE Show details 6 Subspace Gaussian Mixture Models for speech recognition Povey, Daniel; Burget, Lukas; Agarwal, Mohit... In: http://infoscience.epfl.ch/record/203448 (2014) BASE Show details 7 Multilingual acoustic modeling for speech recognition based on subspace Gaussian Mixture Models Burget, Lukas; Schwarz, Petr; Agarwal, Mohit; Akyazi, Pinar; Feng, Kai; Ghoshal, Arnab; Glembek, Ondrej; Goel, Nagendra; Karafiat, Martin; Povey, Daniel; Rastrow, Ariya; Rose, Richard C.; Thomas, Samuel In: http://infoscience.epfl.ch/record/203450 (2014) Abstract: Although research has previously been done on multilingual speech recognition, it has been found to be very difficult to improve over separately trained systems. The usual approach has been to use some kind of “universal phone set” that covers multiple languages. We report experiments on a different approach to multilingual speech recognition, in which the phone sets are entirely distinct but the model has parameters not tied to specific states that are shared across languages. We use a model called a “Subspace Gaussian Mixture Model” where states' distributions are Gaussian Mixture Models with a common structure, constrained to lie in a subspace of the total parameter space. The parameters that define this subspace can be shared across languages. We obtain substantial WER improvements with this approach, especially with very small amounts of in-language training data. URL: http://infoscience.epfl.ch/record/203450 https://doi.org/10.1109/ICASSP.2010.5495646 BASE Hide details 8 Transcribing meetings with the AMIDA systems Grézl, František; Karafiát, Martin; Hain, Thomas... In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 20 (2012) 2, 486-498 BLLDB OLC Linguistik Show details 9 The subspace Gaussian mixture model - a structured model for speech recognition Akyazı, Pınar; Thomas, Samuel; Schwarz, Petr... In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 25 (2011) 2, 404-439 BLLDB OLC Linguistik Show details 10 Fusion of heterogeneous speaker recognition systems in the STBU submission for the NIST speaker recognition evaluation 2006 Matějka, Pavel; Grézl, František; Karafiát, Martin... In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 15 (2007) 7, 2072-2084 BLLDB OLC Linguistik Show details

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