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A Template-Based Approach for Speech Synthesis Intonation Generation Using LSTMs.

, , , and . INTERSPEECH, page 2463-2467. ISCA, (2016)

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Are we using enough listeners? no! - an empirically-supported critique of interspeech 2014 TTS evaluations., , and . INTERSPEECH, page 3476-3480. ISCA, (2015)A Hierarchical Predictor of Synthetic Speech Naturalness Using Neural Networks., , , , , and . INTERSPEECH, page 342-346. ISCA, (2016)On the Importance of Representations for Speech-Driven Gesture Generation., , , , and . AAMAS, page 2072-2074. International Foundation for Autonomous Agents and Multiagent Systems, (2019)Intermediate-State HMMs to Capture Continuously-Changing Signal Features., and . INTERSPEECH, page 1817-1820. ISCA, (2011)From HMMS to DNNS: Where do the improvements come from?, , , , and . ICASSP, page 5505-5509. IEEE, (2016)Analysing Shortcomings of Statistical Parametric Speech Synthesis., , , and . CoRR, (2018)Kernel Density Estimation-Based Markov Models with Hidden State., , and . CoRR, (2018)Analyzing Input and Output Representations for Speech-Driven Gesture Generation., , , , and . IVA, page 97-104. ACM, (2019)Enhancing Subjective Speech Intelligibility Using a Statistical Model of Speech., , and . INTERSPEECH, page 166-169. ISCA, (2012)Minimum Entropy Rate Simplification of Stochastic Processes., and . IEEE Trans. Pattern Anal. Mach. Intell., 38 (12): 2487-2500 (2016)