163 citations · 430 across the 29 of their papers we have counts for
14 papers · 1 filter
Investigating Group Relative Policy Optimization for Diffusion Transformer based Text-to-Audio Generation
Yi Gu, Yanqing Liu, Chen Yang +1
Text-to-audio (T2A) generation has advanced considerably in recent years, yet existing methods continue to face challenges in accurately rendering complex text prompts, particularl…
Boosting Diffusion Model for Spectrogram Up-sampling in Text-to-speech: An Empirical Study
Chong Zhang, Yanqing Liu, Yang Zheng +1
Scaling text-to-speech (TTS) with autoregressive language model (LM) to large-scale datasets by quantizing waveform into discrete speech tokens is making great progress to capture…
E2 TTS: Embarrassingly Easy Fully Non-Autoregressive Zero-Shot TTS
Sefik Emre Eskimez, Xiaofei Wang, Manthan Thakker +10
This paper introduces Embarrassingly Easy Text-to-Speech (E2 TTS), a fully non-autoregressive zero-shot text-to-speech system that offers human-level naturalness and state-of-the-a…
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen +16
While recent large-scale text-to-speech (TTS) models have achieved significant progress, they still fall short in speech quality, similarity, and prosody. Considering speech intric…
Making Flow-Matching-Based Zero-Shot Text-to-Speech Laugh as You Like
Naoyuki Kanda, Xiaofei Wang, Sefik Emre Eskimez +12
Laughter is one of the most expressive and natural aspects of human speech, conveying emotions, social cues, and humor. However, most text-to-speech (TTS) systems lack the ability…
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen +12
Speech conveys more information than text, as the same word can be uttered in various voices to convey diverse information. Compared to traditional text-to-speech (TTS) methods rel…
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan +6
Scaling text-to-speech (TTS) to large-scale, multi-speaker, and in-the-wild datasets is important to capture the diversity in human speech such as speaker identities, prosodies, an…
FoundationTTS: Text-to-Speech for ASR Customization with Generative Language Model
Ruiqing Xue, Yanqing Liu, Lei He +4
Neural text-to-speech (TTS) generally consists of cascaded architecture with separately optimized acoustic model and vocoder, or end-to-end architecture with continuous mel-spectro…
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…
AdaSpeech: Adaptive Text to Speech for Custom Voice
Mingjian Chen, Xu Tan, Bohan Li +4
Custom voice, a specific text to speech (TTS) service in commercial speech platforms, aims to adapt a source TTS model to synthesize personal voice for a target speaker using few s…
Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability
Jinyu Li, Rui Zhao, Zhong Meng +8
Because of its streaming nature, recurrent neural network transducer (RNN-T) is a very promising end-to-end (E2E) model that may replace the popular hybrid model for automatic spee…
MoBoAligner: a Neural Alignment Model for Non-autoregressive TTS with Monotonic Boundary Search
Naihan Li, Shujie Liu, Yanqing Liu +3
To speed up the inference of neural speech synthesis, non-autoregressive models receive increasing attention recently. In non-autoregressive models, additional durations of text to…