I-vector based representation of highly imperfect automatic transcriptions - researchr publication related

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Mohamed Morchid, Mohamed Bouallegue, Richard Dufour, Georges Linarès, Driss Matrouf, Renato de Mori. I-vector based representation of highly imperfect automatic transcriptions. In Haizhou Li, Helen M. Meng, Bin Ma, Eng Siong Chng, Lei Xie, editors, INTERSPEECH 2014, 15th Annual Conference of the International Speech Communication Association, Singapore, September 14-18, 2014. pages 1870-1874, ISCA, 2014. [doi]

The following publications are possibly variants of this publication:

A LDA-BASED TOPIC CLASSIFICATION APPROACH FROM HIGHLY IMPERFECT AUTOMATIC TRANSCRIPTIONSMohamed Morchid, Richard Dufour, Georges Linares. lrec 2014: 1309-1314 [doi]

Latent Topic Model Based Representations for a Robust Theme Identification of Highly Imperfect Automatic TranscriptionsMohamed Morchid, Richard Dufour, Georges Linarès, Youssef Hamadi. cicling 2015: 596-605 [doi]

Topic-space based setup of a neural network for theme identification of highly imperfect transcriptionsMohamed Morchid, Richard Dufour, Georges Linarès. asru 2015: 346-352 [doi]

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