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Reformulating the HMM as a trajectory model by imposing explicit relationships between static and dynamic feature vector sequences

, , and . Computer Speech & Language, 21 (1): 153-173 (January 2007)
DOI: 10.1016/j.csl.2006.01.002

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Discriminative Feature Extraction Based on Sequential Variational Autoencoder for Speaker Recognition., , , , , and . APSIPA, page 1742-1746. IEEE, (2018)Image Recognition Based on Convolutional Neural Networks Using Features Generated from Separable Lattice Hidden Markov Models., , , , , , and . APSIPA, page 324-328. IEEE, (2018)HMM-Based singing voice synthesis and its application to Japanese and English., , , and . ICASSP, page 265-269. IEEE, (2014)Parameter sharing and minimum classification error training of mixtures of factor analyzers for speaker identification., , , , and . ICASSP (1), page 29-32. IEEE, (2004)Speech recognition using voice-characteristic-dependent acoustic models., , , , , and . ICASSP (1), page 740-743. IEEE, (2003)Mmdagent - A fully open-source toolkit for voice interaction systems., , and . ICASSP, page 8382-8385. IEEE, (2013)User Generated Dialogue Systems: uDialogue., , , , , , , , , and 1 other author(s). Human-Harmonized Information Technology (2), Springer, (2017)A Bayesian Approach to Image Recognition Based on Separable Lattice Hidden Markov Models., , , , and . IEICE Trans. Inf. Syst., 99-D (12): 3119-3131 (2016)State Duration Modeling for HMM-Based Speech Synthesis., , , , , and . IEICE Trans. Inf. Syst., 90-D (3): 692-693 (2007)Adaptive cepstral analysis of speech., , and . IEEE Trans. Speech Audio Process., 3 (6): 481-489 (1995)