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20192026
most citedDurIAN: Duration Informed Attention Network For Multimodal Synthesis

94 citations · 129 across the 21 of their papers we have counts for

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7 papers · 1 filter

eess.AS2026

SemaVoice: Semantic-Aware Continuous Autoregressive Speech Synthesis

Huimeng Wang, Hui Lu, Jiajun Deng +7

Continuous autoregressive speech synthesis has recently emerged as a promising direction for zero-shot text-to-speech (TTS). However, existing methods still suffer from a fundament…

eess.AS2025

Disambiguation of Chinese Polyphones in an End-to-End Framework with Semantic Features Extracted by Pre-trained BERT

Dongyang Dai, Zhiyong Wu, Shiyin Kang +5

Grapheme-to-phoneme (G2P) conversion serves as an essential component in Chinese Mandarin text-to-speech (TTS) system, where polyphone disambiguation is the core issue. In this pap…

eess.AS2021★ 3 cited

Adversarially learning disentangled speech representations for robust multi-factor voice conversion

Jie Wang, Jingbei Li, Xintao Zhao +3

Factorizing speech as disentangled speech representations is vital to achieve highly controllable style transfer in voice conversion (VC). Conventional speech representation learni…

eess.AS2020★ 3 cited

Speaker Independent and Multilingual/Mixlingual Speech-Driven Talking Head Generation Using Phonetic Posteriorgrams

Huirong Huang, Zhiyong Wu, Shiyin Kang +9

Generating 3D speech-driven talking head has received more and more attention in recent years. Recent approaches mainly have following limitations: 1) most speaker-independent meth…

eess.AS2020★ 2 cited

Transferring Source Style in Non-Parallel Voice Conversion

Songxiang Liu, Yuewen Cao, Shiyin Kang +5

Voice conversion (VC) techniques aim to modify speaker identity of an utterance while preserving the underlying linguistic information. Most VC approaches ignore modeling of the sp…

eess.AS2020★ 10 cited

Audio-visual Recognition of Overlapped speech for the LRS2 dataset

Jianwei Yu, Shi-Xiong Zhang, Jian Wu +7

Automatic recognition of overlapped speech remains a highly challenging task to date. Motivated by the bimodal nature of human speech perception, this paper investigates the use of…

eess.AS2019★ 13 cited

Maximizing Mutual Information for Tacotron

Peng Liu, Xixin Wu, Shiyin Kang +3

End-to-end speech synthesis methods already achieve close-to-human quality performance. However compared to HMM-based and NN-based frame-to-frame regression methods, they are prone…