2 citations · 3 across the 10 of their papers we have counts for
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FineCombo-TTS: Collaborative and Precise Controllable Speech Synthesis Using Text Descriptions and Reference Speech
Shuoyi Zhou, Yixuan Zhou, Peiji Yang +4
Controllable text-to-speech (TTS) has become a key research focus. However, methods based on either reference speech or text descriptions lack flexibility and precise control, and…
HPSU: A Benchmark for Human-Level Perception in Real-World Spoken Speech Understanding
Chen Li, Peiji Yang, Yicheng Zhong +5
Recent advances in Speech Large Language Models (Speech LLMs) have led to great progress in speech understanding tasks such as Automatic Speech Recognition (ASR) and Speech Emotion…
Multi-Reward GRPO for Stable and Prosodic Single-Codebook TTS LLMs at Scale
Yicheng Zhong, Peiji Yang, Zhisheng Wang
Recent advances in Large Language Models (LLMs) have transformed text-to-speech (TTS) synthesis, inspiring autoregressive frameworks that represent speech as sequences of discrete…
Optimizing Neural Speech Codec for Low-Bitrate Compression via Multi-Scale Encoding
Peiji Yang, Fengping Wang, Yicheng Zhong +2
Neural speech codecs have demonstrated their ability to compress high-quality speech and audio by converting them into discrete token representations. Most existing methods utilize…
Spontaneous Style Text-to-Speech Synthesis with Controllable Spontaneous Behaviors Based on Language Models
Weiqin Li, Peiji Yang, Yicheng Zhong +5
Spontaneous style speech synthesis, which aims to generate human-like speech, often encounters challenges due to the scarcity of high-quality data and limitations in model capabili…
AccentSpeech: Learning Accent from Crowd-sourced Data for Target Speaker TTS with Accents
Yongmao Zhang, Zhichao Wang, Peiji Yang +3
Learning accent from crowd-sourced data is a feasible way to achieve a target speaker TTS system that can synthesize accent speech. To this end, there are two challenging problems…