102 citations · 119 across the 17 of their papers we have counts for
21 papers
AuraSE: Low-Hallucination Generative Speech Enhancement via Multimodal Flow Matching and Inference Policy Optimization
Yingda Shen, Yao Qian, Yuxuan Hu +7
Generative speech enhancement models can produce cleaner and more natural-sounding speech than conventional discriminative approaches, but may hallucinate by changing speech conten…
EchoChat: Structured Cognitive Reasoning in Empathetic Spoken Dialogue
Dingdong Wang, Shujie Liu, Yayue Deng +6
Empathetic spoken dialogue is a sophisticated cognitive process that requires not only recognizing emotions but also inferring a user's latent mental states to provide appropriate…
DuraS2ST: Chain-of-Thought and Reinforcement Learning for Duration-Aligned Speech-to-Speech Translation
Yayue Deng, Dingdong Wang, Yuxuan Hu +7
Speech-to-speech translation (S2ST) in time-sensitive applications such as video dubbing requires not only semantic fidelity and speaker preservation, but also strict duration cons…
Rethinking Speech-LLM Integration for ASR: Effective Joint Speech-Text Training by Interleaving
Ruchao Fan, Yiming Wang, Rui Zhao +10
Speech-LLM integration has shown promising results by leveraging extensive textual pretraining, yet its specific benefits for automatic speech recognition (ASR) remain unclear. We…
LLM can Read Spectrogram: Encoder-free Speech-Language Modeling
Ruchao Fan, Yiming Wang, Yuxuan Hu +6
Recent speech-aware large language models (Speech-LLMs) rely on pre-trained speech encoders to convert audio into semantic/acoustic rich representations consumable by LLM. In this…
Preserving Speech-to-Text LLM Capabilities in Speech-to-Speech Generation
Yuxuan Hu, Heng Lu, Ruchao Fan +8
Strong speech-to-text (S2T) LLMs already provide robust speech perception and text reasoning, but adding speech-to-speech (S2S) output is challenging: fine-tuning the backbone can…
Is Text All You Need? Text as a Universal Information Bottleneck for Speech LLMs
Ming-Hao Hsu, Yuxuan Hu, Shujie Liu +3
Large language models (LLMs) provide a powerful reasoning backbone for speech understanding, but integrating continuous acoustic signals into a pretrained LLM remains challenging.…
FlexiCodec: A Dynamic Neural Audio Codec for Low Frame Rates
Jiaqi Li, Yao Qian, Yuxuan Hu +7
Neural audio codecs are foundational to speech language models. It is expected to have a low frame rate and decoupled semantic and acoustic information. A lower frame rate codec ca…
Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Haibin Wu, Yuxuan Hu, Ruchao Fan +8
Speech language models (Speech LMs) enable end-to-end speech-text modeling within a single model, offering a promising direction for spoken dialogue systems. The choice of speech-t…
SLM-S2ST: A multimodal language model for direct speech-to-speech translation
Yuxuan Hu, Haibin Wu, Ruchao Fan +4
Speech-aware language models (LMs) have demonstrated capabilities in understanding spoken language while generating text-based responses. However, enabling them to produce speech o…
CoVoMix2: Advancing Zero-Shot Dialogue Generation with Fully Non-Autoregressive Flow Matching
Leying Zhang, Yao Qian, Xiaofei Wang +8
Generating natural-sounding, multi-speaker dialogue is crucial for applications such as podcast creation, virtual agents, and multimedia content generation. However, existing syste…
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…
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…
AlignFormer: Modality Matching Can Achieve Better Zero-shot Instruction-Following Speech-LLM
Ruchao Fan, Bo Ren, Yuxuan Hu +3
Integrating speech into LLM (speech-LLM) has gaining increased attention recently. The mainstream solution is to connect a well-trained speech encoder and LLM with a neural adapter…
Adapting Large Language Model with Speech for Fully Formatted End-to-End Speech Recognition
Shaoshi Ling, Yuxuan Hu, Shuangbei Qian +5
Most end-to-end (E2E) speech recognition models are composed of encoder and decoder blocks that perform acoustic and language modeling functions. Pretrained large language models (…
Code-Switching Text Generation and Injection in Mandarin-English ASR
Haibin Yu, Yuxuan Hu, Yao Qian +7
Code-switching speech refers to a means of expression by mixing two or more languages within a single utterance. Automatic Speech Recognition (ASR) with End-to-End (E2E) modeling f…
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
Eric Sun, Jinyu Li, Yuxuan Hu +8
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users dur…
CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network
Yanlin Wang, Ensheng Shi, Lun Du +5
Source code summaries are short natural language descriptions of code snippets that help developers better understand and maintain source code. There has been a surge of work on au…
Improving Transformer-based Speech Recognition Using Unsupervised Pre-training
Dongwei Jiang, Xiaoning Lei, Wubo Li +4
Speech recognition technologies are gaining enormous popularity in various industrial applications. However, building a good speech recognition system usually requires large amount…