163 citations · 430 across the 29 of their papers we have counts for
5 papers · 1 filter
DelightfulTTS 2: End-to-End Speech Synthesis with Adversarial Vector-Quantized Auto-Encoders
Yanqing Liu, Ruiqing Xue, Lei He +2
Current text to speech (TTS) systems usually leverage a cascaded acoustic model and vocoder pipeline with mel-spectrograms as the intermediate representations, which suffer from tw…
RetrieverTTS: Modeling Decomposed Factors for Text-Based Speech Insertion
Dacheng Yin, Chuanxin Tang, Yanqing Liu +6
This paper proposes a new "decompose-and-edit" paradigm for the text-based speech insertion task that facilitates arbitrary-length speech insertion and even full sentence generatio…
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
Xu Tan, Jiawei Chen, Haohe Liu +11
Text to speech (TTS) has made rapid progress in both academia and industry in recent years. Some questions naturally arise that whether a TTS system can achieve human-level quality…
Mixed-Phoneme BERT: Improving BERT with Mixed Phoneme and Sup-Phoneme Representations for Text to Speech
Guangyan Zhang, Kaitao Song, Xu Tan +8
Recently, leveraging BERT pre-training to improve the phoneme encoder in text to speech (TTS) has drawn increasing attention. However, the works apply pre-training with character-b…
Towards Contextual Spelling Correction for Customization of End-to-end Speech Recognition Systems
Xiaoqiang Wang, Yanqing Liu, Jinyu Li +3
Contextual biasing is an important and challenging task for end-to-end automatic speech recognition (ASR) systems, which aims to achieve better recognition performance by biasing t…