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Investigation of multilingual deep neural networks for spoken term detection.

, , , , , and . ASRU, page 138-143. IEEE, (2013)

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Data augmentation for low resource languages., , , and . INTERSPEECH, page 810-814. ISCA, (2014)A region-specific feature-space transformation for speaker adaptation and singularity analysis of jacobian matrix., , , , and . INTERSPEECH, page 1228-1232. ISCA, (2013)A computationally efficient approach for acoustic class specific VTLN using regression tree.. I. J. Speech Technology, 21 (3): 641-647 (2018)Teager Energy Subband Filtered Features for Near and Far-Field Automatic Speech Recognition., , , , , and . APSIPA ASC, page 491-496. IEEE, (2021)A factorized representation of FMLLR transform based on QR-decomposition., , , and . INTERSPEECH, page 551-554. ISCA, (2012)Language independent and unsupervised acoustic models for speech recognition and keyword spotting., , , and . INTERSPEECH, page 16-20. ISCA, (2014)Investigation of multilingual deep neural networks for spoken term detection., , , , , and . ASRU, page 138-143. IEEE, (2013)Joint Distribution Learning in the Framework of Variational Autoencoders for Far-Field Speech Enhancement., , and . ASRU, page 245-251. IEEE, (2019)A Multi-Accent Acoustic Model Using Mixture of Experts for Speech Recognition., , and . INTERSPEECH, page 779-783. ISCA, (2019)Combining tandem and hybrid systems for improved speech recognition and keyword spotting on low resource languages., , , and . INTERSPEECH, page 835-839. ISCA, (2014)