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Statistical acoustic-to-articulatory mapping unified with speaker normalization based on voice conversion.

, , , and . INTERSPEECH, page 588-592. ISCA, (2015)

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Statistical acoustic-to-articulatory mapping unified with speaker normalization based on voice conversion., , , and . INTERSPEECH, page 588-592. ISCA, (2015)Acoustic-to-Articulatory Mapping Based on Mixture of Probabilistic Canonical Correlation Analysis., , and . INTERSPEECH, page 989-993. ISCA, (2017)A pairwise learning strategy for video-based face recognition., , , , , and . CVPR Workshops, Computer Vision Foundation / IEEE, (2019)Parallel-Data-Free Many-to-Many Voice Conversion Based on DNN Integrated with Eigenspace Using a Non-Parallel Speech Corpus., , , and . INTERSPEECH, page 1278-1282. ISCA, (2017)Voice Conversion Based on Matrix Variate Gaussian Mixture Model Using Multiple Frame Features., , , and . INTERSPEECH, page 302-306. ISCA, (2016)A study on the improvement of measurement accuracy of the three-dimensional electromagnetic articulography., , and . INTERSPEECH, page 726-730. ISCA, (2014)Prediction of the Articulatory Movements of Unseen Phonemes of a Speaker Using the Speech Structure of Another Speaker., , and . INTERSPEECH, page 450-454. ISCA, (2016)Discover the Effective Strategy for Face Recognition Model Compression by Improved Knowledge Distillation., , , , , and . ICIP, page 2416-2420. IEEE, (2018)