2 citations · 3 across the 10 of their papers we have counts for
10 papers
ReLMCodec: Designing Predictable Speech Tokens from Pre-Quantization Phoneme Structure
Zixiang Wan, Xusheng Yang, Zheng Wang +1
Neural speech codecs face a fundamental tension in the language-model era: tokens that support high-fidelity reconstruction are not necessarily easy for autoregressive models to pr…
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…
TellWhisper: Tell Whisper Who Speaks When
Yifan Hu, Peiji Yang, Zhisheng Wang +2
Multi-speaker automatic speech recognition (MASR) aims to predict ''who spoke when and what'' from multi-speaker speech, a key technology for multi-party dialogue understanding. Ho…
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…
ExpCLIP: Bridging Text and Facial Expressions via Semantic Alignment
Yicheng Zhong, Huawei Wei, Peiji Yang +1
The objective of stylized speech-driven facial animation is to create animations that encapsulate specific emotional expressions. Existing methods often depend on pre-established e…
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…
Cross-lingual Text Classification with Heterogeneous Graph Neural Network
Ziyun Wang, Xuan Liu, Peiji Yang +2
Cross-lingual text classification aims at training a classifier on the source language and transferring the knowledge to target languages, which is very useful for low-resource lan…