8 papers
StreamMel: Real-Time Zero-shot Text-to-Speech via Interleaved Continuous Autoregressive Modeling
Hui Wang, Yifan Yang, Shujie Liu +7
Recent advances in zero-shot text-to-speech (TTS) synthesis have achieved high-quality speech generation for unseen speakers, but most systems remain unsuitable for real-time appli…
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…
Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs
Microsoft, :, Abdelrahman Abouelenin +73
We introduce Phi-4-Mini and Phi-4-Multimodal, compact yet highly capable language and multimodal models. Phi-4-Mini is a 3.8-billion-parameter language model trained on high-qualit…
FELLE: Autoregressive Speech Synthesis with Token-Wise Coarse-to-Fine Flow Matching
Hui Wang, Shujie Liu, Lingwei Meng +9
To advance continuous-valued token modeling and temporal-coherence enforcement, we propose FELLE, an autoregressive model that integrates language modeling with token-wise flow mat…
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…
Interleaved Speech-Text Language Models for Simple Streaming Text-to-Speech Synthesis
Yifan Yang, Shujie Liu, Jinyu Li +10
This paper introduces Interleaved Speech-Text Language Model (IST-LM) for zero-shot streaming Text-to-Speech (TTS). Unlike many previous approaches, IST-LM is directly trained on i…