Neural HMMs are all you need (for high-quality attention-free TTS)

Neural HMMs are all you need (for high-quality attention-free TTS)

30 August 2021

Papers citing "Neural HMMs are all you need (for high-quality attention-free TTS)"

11 / 11 papers shown

Title
Source Tracing of Audio Deepfake Systems Nicholas Klein Tianxiang Chen Hemlata Tak Ricardo Casal Elie Khoury 32 4 0 10 Jul 2024
Should you use a probabilistic duration model in TTS? Probably! Especially for spontaneous speech Shivam Mehta Harm Lameris Rajiv Punmiya Jonas Beskow Éva Székely G. Henter 25 1 0 08 Jun 2024
Fake it to make it: Using synthetic data to remedy the data shortage in joint multimodal speech-and-gesture synthesis Shivam Mehta Anna Deichler Jim O'Regan Birger Moëll Jonas Beskow G. Henter Simon Alexanderson 46 4 0 30 Apr 2024
Pyramidal Hidden Markov Model For Multivariate Time Series Forecasting YeXin Huang AI4TS 25 0 0 22 Oct 2023
Matcha-TTS: A fast TTS architecture with conditional flow matching Shivam Mehta Ruibo Tu Jonas Beskow Éva Székely G. Henter 16 69 0 06 Sep 2023
Diff-TTSG: Denoising probabilistic integrated speech and gesture synthesis Shivam Mehta Siyang Wang Simon Alexanderson Jonas Beskow Éva Székely G. Henter DiffM 26 14 0 15 Jun 2023
Prosody-controllable spontaneous TTS with neural HMMs Harm Lameris Shivam Mehta G. Henter Joakim Gustafson Éva Székely 33 15 0 24 Nov 2022
OverFlow: Putting flows on top of neural transducers for better TTS Shivam Mehta Ambika Kirkland Harm Lameris Jonas Beskow Éva Székely G. Henter AI4TS 34 12 0 13 Nov 2022
The Importance of Accurate Alignments in End-to-End Speech Synthesis Anusha Prakash H. Murthy 21 0 0 31 Oct 2022
R-MelNet: Reduced Mel-Spectral Modeling for Neural TTS Kyle Kastner Aaron Courville 27 0 0 30 Jun 2022
End-to-End Text-to-Speech using Latent Duration based on VQ-VAE Yusuke Yasuda Xin Wang Junichi Yamagishi 13 16 0 19 Oct 2020