7 citations · 26 across the 35 of their papers we have counts for
13 papers · 1 filter
Joint Learning Global-Local Speaker Classification to Enhance End-to-End Speaker Diarization and Recognition
Yuhang Dai, Haopeng Lin, Jiale Qian +9
Large Audio-Language Models (LALMs) have demonstrated remarkable performance in end-to-end speaker diarization and recognition. However, their speaker discriminability remains limi…
The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Era
Zhixian Zhao, Shuiyuan Wang, Guojian Li +12
Driven by the rapid advancement of Large Language Models (LLMs), particularly Audio-LLMs and Omni-models, spoken dialogue systems have evolved significantly, progressively narrowin…
UniSS: Unified Expressive Speech-to-Speech Translation with Your Voice
Sitong Cheng, Weizhen Bian, Xinsheng Wang +5
The ultimate goal of expressive speech-to-speech translation (S2ST) is to accurately translate spoken content while preserving the speaker identity and emotional style. However, pr…
Spark-TTS: An Efficient LLM-Based Text-to-Speech Model with Single-Stream Decoupled Speech Tokens
Xinsheng Wang, Mingqi Jiang, Ziyang Ma +22
Recent advancements in large language models (LLMs) have driven significant progress in zero-shot text-to-speech (TTS) synthesis. However, existing foundation models rely on multi-…
Steering Language Model to Stable Speech Emotion Recognition via Contextual Perception and Chain of Thought
Zhixian Zhao, Xinfa Zhu, Xinsheng Wang +4
Large-scale audio language models (ALMs), such as Qwen2-Audio, are capable of comprehending diverse audio signal, performing audio analysis and generating textual responses. Howeve…
Audio-FLAN: An Instruction-Following Dataset for Unified Audio Understanding and Generation of Speech, Music, and Sound
Liumeng Xue, Ziya Zhou, Jiahao Pan +20
Recent advancements in audio tokenization have significantly enhanced the integration of audio capabilities into large language models (LLMs). However, audio understanding and gene…
UniSyn: An End-to-End Unified Model for Text-to-Speech and Singing Voice Synthesis
Yi Lei, Shan Yang, Xinsheng Wang +4
Text-to-speech (TTS) and singing voice synthesis (SVS) aim at generating high-quality speaking and singing voice according to textual input and music scores, respectively. Unifying…
Cross-speaker Emotion Transfer Based On Prosody Compensation for End-to-End Speech Synthesis
Tao Li, Xinsheng Wang, Qicong Xie +3
Cross-speaker emotion transfer speech synthesis aims to synthesize emotional speech for a target speaker by transferring the emotion from reference speech recorded by another (sour…
AdaVITS: Tiny VITS for Low Computing Resource Speaker Adaptation
Kun Song, Heyang Xue, Xinsheng Wang +6
Speaker adaptation in text-to-speech synthesis (TTS) is to finetune a pre-trained TTS model to adapt to new target speakers with limited data. While much effort has been conducted…
Learn2Sing 2.0: Diffusion and Mutual Information-Based Target Speaker SVS by Learning from Singing Teacher
Heyang Xue, Xinsheng Wang, Yongmao Zhang +3
Building a high-quality singing corpus for a person who is not good at singing is non-trivial, thus making it challenging to create a singing voice synthesizer for this person. Lea…
Opencpop: A High-Quality Open Source Chinese Popular Song Corpus for Singing Voice Synthesis
Yu Wang, Xinsheng Wang, Pengcheng Zhu +6
This paper introduces Opencpop, a publicly available high-quality Mandarin singing corpus designed for singing voice synthesis (SVS). The corpus consists of 100 popular Mandarin so…
MsEmoTTS: Multi-scale emotion transfer, prediction, and control for emotional speech synthesis
Yi Lei, Shan Yang, Xinsheng Wang +1
Expressive synthetic speech is essential for many human-computer interaction and audio broadcast scenarios, and thus synthesizing expressive speech has attracted much attention in…
Cross-speaker emotion disentangling and transfer for end-to-end speech synthesis
Tao Li, Xinsheng Wang, Qicong Xie +2
The cross-speaker emotion transfer task in text-to-speech (TTS) synthesis particularly aims to synthesize speech for a target speaker with the emotion transferred from reference sp…