3 citations · 8 across the 24 of their papers we have counts for
12 papers · 1 filter
GigaSpeechBench: A Real-World Multilingual Speech-to-Text Benchmark
Yujie Tu, Yifan Yang, Tianrui Wang +35
While modern ASR systems achieve low error rates on high-resource benchmarks, such performance often overestimates real-world robustness. Existing evaluations address challenges in…
X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System
Yuxiang Zhao, Yichi Zhang, Yanjie An +10
Real-time speech-to-speech translation (S2ST) systems must balance translation quality, latency, speech naturalness, and speaker consistency. Publicly documented S2ST systems have…
Anonymization, Not Elimination: Utility-Preserved Speech Anonymization
Yunchong Xiao, Yuxiang Zhao, Ziyang Ma +4
The growing reliance on large-scale speech data has made privacy protection a critical concern. However, existing anonymization approaches often degrade data utility, for example b…
X-VC: Zero-shot Streaming Voice Conversion in Codec Space
Qixi Zheng, Yuxiang Zhao, Tianrui Wang +7
Zero-shot voice conversion (VC) aims to convert a source utterance into the voice of an unseen target speaker while preserving its linguistic content. Although recent systems have…
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…
UltraVoice: Scaling Fine-Grained Style-Controlled Speech Conversations for Spoken Dialogue Models
Wenming Tu, Guanrou Yang, Ruiqi Yan +6
Spoken dialogue models currently lack the ability for fine-grained speech style control, a critical capability for human-like interaction that is often overlooked in favor of purel…
Traceable TTS: Toward Watermark-Free TTS with Strong Traceability
Yuxiang Zhao, Yunchong Xiao, Yushen Chen +4
Recent advances in Text-To-Speech (TTS) technology have enabled synthetic speech to mimic human voices with remarkable realism, raising significant security concerns. This undersco…
Accelerating Flow-Matching-Based Text-to-Speech via Empirically Pruned Step Sampling
Qixi Zheng, Yushen Chen, Zhikang Niu +4
Flow-matching-based text-to-speech (TTS) models, such as Voicebox, E2 TTS, and F5-TTS, have attracted significant attention in recent years. These models require multiple sampling…
Pseudo-Autoregressive Neural Codec Language Models for Efficient Zero-Shot Text-to-Speech Synthesis
Yifan Yang, Shujie Liu, Jinyu Li +10
Recent zero-shot text-to-speech (TTS) systems face a common dilemma: autoregressive (AR) models suffer from slow generation and lack duration controllability, while non-autoregress…
SLAM-Omni: Timbre-Controllable Voice Interaction System with Single-Stage Training
Wenxi Chen, Ziyang Ma, Ruiqi Yan +13
Recent advancements highlight the potential of end-to-end real-time spoken dialogue systems, showcasing their low latency and high quality. In this paper, we introduce SLAM-Omni, a…
SLAM-AAC: Enhancing Audio Captioning with Paraphrasing Augmentation and CLAP-Refine through LLMs
Wenxi Chen, Ziyang Ma, Xiquan Li +5
Automated Audio Captioning (AAC) aims to generate natural textual descriptions for input audio signals. Recent progress in audio pre-trained models and large language models (LLMs)…
F5-TTS: A Fairytaler that Fakes Fluent and Faithful Speech with Flow Matching
Yushen Chen, Zhikang Niu, Ziyang Ma +5
This paper introduces F5-TTS, a fully non-autoregressive text-to-speech system based on flow matching with Diffusion Transformer (DiT). Without requiring complex designs such as du…