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StreamTN is proposed, a lightweight LLM-based Chinese streaming TN model that employs a dual-track streaming framework in which input tokens and output tokens are processed on two parallel tracks, enabling low-latency real-time inference without complex prompting.
MeanVC 2 cuts voice conversion latency in half while enhancing robustness to low-quality audio references, revolutionizing real-time voice applications.
FlashTTS slashes First-Packet Latency to 325ms, revolutionizing real-time speech dialogue systems without sacrificing voice quality.
Achieving high accuracy in multi-speaker transcription, SoulX-Transcriber outperforms existing models by effectively addressing speaker overlap and rapid turn-taking.
Open-source TTS models can beat commercial systems in specific languages, but current instruction-following TTS still struggles with complex instructions like nuanced paralinguistic controls.
Achieve human-like full-duplex voice interactions with SoulX-Duplug, a plug-and-play module that slashes latency and improves turn management by acting as a semantic VAD.