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Automatic glottal inverse filtering with the Markov chain Monte Carlo method.

, , , , , и . Comput. Speech Lang., 28 (5): 1139-1155 (2014)

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Tuomo Fonsén

Tuomo Takkula

Juha Tuomo Tapio Ylä-Jääski

 

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Parametric Representation for Singing Voice Synthesis: a Comparative Evaluation., , , , и . CoRR, (2020)Toward a Universal Synthetic Speech Spoofing Detection Using Phase Information., , , , , и . IEEE Trans. Inf. Forensics Secur., 10 (4): 810-820 (2015)Voice source analysis using biomechanical modeling and glottal inverse filtering., , , и . INTERSPEECH, стр. 1604-1607. ISCA, (2012)Prediction of creaky voice from contextual factors., , , и . ICASSP, стр. 7967-7971. IEEE, (2013)Phase perception of the glottal excitation and its relevance in statistical parametric speech synthesis., , , , и . Speech Commun., (2016)Excitation modeling for HMM-based speech synthesis: Breaking down the impact of periodic and aperiodic components., и . ICASSP, стр. 260-264. IEEE, (2014)Lombard modified text-to-speech synthesis for improved intelligibility: submission for the hurricane challenge 2013., , , , , и . INTERSPEECH, стр. 3562-3566. ISCA, (2013)Deep neural network based trainable voice source model for synthesis of speech with varying vocal effort., , , , и . INTERSPEECH, стр. 1969-1973. ISCA, (2014)Utilizing Markov Chain Monte Carlo (MCMC) Method for Improved Glottal Inverse Filtering., , , и . INTERSPEECH, стр. 1640-1643. ISCA, (2012)Emphasis Control for Parallel Neural TTS., , , и . INTERSPEECH, стр. 3378-3382. ISCA, (2022)