7 citations · 26 across the 35 of their papers we have counts for
37 papers
SemBridge: Semantic Token Anchoring for Continuous-Latent Autoregressive Speech Generation
Hanke Xie, Haopeng Lin, Jiale Qian +13
Continuous-latent autoregressive speech generation has emerged as a promising alternative to discrete-token modeling by avoiding quantization loss and preserving richer acoustic in…
SoulX-Transcriber: A Robust End-to-End Framework for Multi-Speaker Speech Transcription
Yuhang Dai, Haopeng Lin, Zhennan Lin +10
Recent advances in Automatic Speech Recognition (ASR) and Large Language Models (LLMs) have significantly improved speech understanding capabilities. However, multi-speaker speech…
Dual-LoRA: Parameter-Efficient Adversarial Disentanglement for Cross-Lingual Speaker Verification
Qituan Shangguan, Junhao Du, Kunyang Peng +5
Cross-lingual speaker verification suffers from severe language-speaker entanglement. This causes systematic degradation in the hardest scenario: correctly accepting utterances fro…
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…
SoulX-Duplug: Plug-and-Play Streaming State Prediction Module for Realtime Full-Duplex Speech Conversation
Ruiqi Yan, Wenxi Chen, Zhanxun Liu +17
Recent advances in spoken dialogue systems have brought increased attention to human-like full-duplex voice interactions. However, our comprehensive review of this field reveals se…
SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis
Jiale Qian, Hao Meng, Tian Zheng +17
While recent years have witnessed rapid progress in speech synthesis, open-source singing voice synthesis (SVS) systems still face significant barriers to industrial deployment, pa…
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…
SoulX-Podcast: Towards Realistic Long-form Podcasts with Dialectal and Paralinguistic Diversity
Hanke Xie, Haopeng Lin, Wenxiao Cao +17
Recent advances in text-to-speech (TTS) synthesis have significantly improved speech expressiveness and naturalness. However, most existing systems are tailored for single-speaker…
DialoSpeech: Dual-Speaker Dialogue Generation with LLM and Flow Matching
Hanke Xie, Dake Guo, Chengyou Wang +8
Recent advances in text-to-speech (TTS) synthesis, particularly those leveraging large language models (LLMs), have significantly improved expressiveness and naturalness. However,…
SAC: Neural Speech Codec with Semantic-Acoustic Dual-Stream Quantization
Wenxi Chen, Xinsheng Wang, Ruiqi Yan +9
Speech codecs that convert continuous speech signals into discrete tokens have become essential for speech language models. However, existing codecs struggle to balance high-qualit…
Evaluating Bias in Spoken Dialogue LLMs for Real-World Decisions and Recommendations
Yihao Wu, Tianrui Wang, Yizhou Peng +5
While biases in large language models (LLMs), such as stereotypes and cultural tendencies in outputs, have been examined and identified, their presence and characteristics in spoke…
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-…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…
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…
CosyAudio: Improving Audio Generation with Confidence Scores and Synthetic Captions
Xinfa Zhu, Wenjie Tian, Xinsheng Wang +4
Text-to-Audio (TTA) generation is an emerging area within AI-generated content (AIGC), where audio is created from natural language descriptions. Despite growing interest, developi…
EDSep: An Effective Diffusion-Based Method for Speech Source Separation
Jinwei Dong, Xinsheng Wang, Qirong Mao
Generative models have attracted considerable attention for speech separation tasks, and among these, diffusion-based methods are being explored. Despite the notable success of dif…
FleSpeech: Flexibly Controllable Speech Generation with Various Prompts
Hanzhao Li, Yuke Li, Xinsheng Wang +4
Controllable speech generation methods typically rely on single or fixed prompts, hindering creativity and flexibility. These limitations make it difficult to meet specific user ne…
StreamVoice+: Evolving into End-to-end Streaming Zero-shot Voice Conversion
Zhichao Wang, Yuanzhe Chen, Xinsheng Wang +2
StreamVoice has recently pushed the boundaries of zero-shot voice conversion (VC) in the streaming domain. It uses a streamable language model (LM) with a context-aware approach to…
SCDNet: Self-supervised Learning Feature-based Speaker Change Detection
Yue Li, Xinsheng Wang, Li Zhang +1
Speaker Change Detection (SCD) is to identify boundaries among speakers in a conversation. Motivated by the success of fine-tuning wav2vec 2.0 models for the SCD task, a further in…
StreamVoice: Streamable Context-Aware Language Modeling for Real-time Zero-Shot Voice Conversion
Zhichao Wang, Yuanzhe Chen, Xinsheng Wang +2
Recent language model (LM) advancements have showcased impressive zero-shot voice conversion (VC) performance. However, existing LM-based VC models usually apply offline conversion…
MSM-VC: High-fidelity Source Style Transfer for Non-Parallel Voice Conversion by Multi-scale Style Modeling
Zhichao Wang, Xinsheng Wang, Qicong Xie +4
In addition to conveying the linguistic content from source speech to converted speech, maintaining the speaking style of source speech also plays an important role in the voice co…
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…