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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 – 4 of 4 1 Lexical speaker identification in TV shows Roy, Anindya; Bredin, Hervé; Hartmann, William... In: ISSN: 1380-7501 ; EISSN: 1573-7721 ; Multimedia Tools and Applications ; https://hal.archives-ouvertes.fr/hal-01690342 ; Multimedia Tools and Applications, Springer Verlag, 2015, 74 (4), pp.1377 - 1396. ⟨10.1007/s11042-014-1940-3⟩ (2015) BASE Show details 2 TVD: a reproducible and multiply aligned TV series dataset Roy, Anindya; Guinaudeau, Camille; Bredin, Hervé... In: LREC 2014 ; https://hal.archives-ouvertes.fr/hal-01690279 ; LREC 2014, May 2014, Reykjavik, Iceland (2014) BASE Show details 3 Some issues affecting the transcription of hungarian broadcast audio Roy, Anindya; Lamel, Lori; Fraga Da Silva, Thiago... In: Annual Conference of the International Speech Communication Association ; https://hal.archives-ouvertes.fr/hal-01843430 ; Annual Conference of the International Speech Communication Association , Aug 2013, Lyon, France (2013) BASE Show details 4 Acoustic unit discovery and pronunciation generation from a grapheme-based lexicon Hartmann, William; Roy, Anindya; Lamel, Lori; Gauvain, Jean-Luc In: IEEE Automatic Speech Recognition and Understanding Workshop ; https://hal.archives-ouvertes.fr/hal-01843433 ; IEEE Automatic Speech Recognition and Understanding Workshop, Dec 2013, Olomouc, Czech Republic (2013) Abstract: International audience ; We present a framework for discovering acoustic units and generating an associated pronunciation lexicon from an initial grapheme-based recognition system. Our approach consists of two distinct contributions. First, context-dependent grapheme models are clustered using a spectral clustering approach to create a set of phone-like acoustic units. Next, we transform the pronunciation lexicon using a statistical machine translation-based approach. Pronunciation hypotheses generated from a decoding of the training set are used to create a phrase-based translation table. We propose a novel method for scoring the phrase-based rules that significantly improves the output of the transformation process. Results on an English language dataset demonstrate the combined methods provide a 13% relative reduction in word error rate compared to a baseline grapheme-based system. Our approach could potentially be applied to low-resource languages without existing lexicons, such as in the Babel project. Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO]Computer Science [cs] URL: https://hal.archives-ouvertes.fr/hal-01843433 BASE Hide details

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