3 citations · 5 across the 21 of their papers we have counts for
24 papers
MMAE: A Massive Multitask Audio Editing Benchmark
Ziyang Ma, Ruiqi Yan, Ruiyang Xu +35
We introduce MMAE, a Massive Multitask Audio Editing benchmark, serving as the first comprehensive evaluation testbed designed for general-purpose instruction-based audio editing.…
WavTTS: Towards High-Quality Zero-Shot TTS via Direct Raw Waveform Modeling
Wenxi Chen, Dongya Jia, Yushen Chen +11
Recently, diffusion models operating on VAE latents or mel-spectrograms have become the dominant paradigm for zero-shot TTS. Although these compressed representations improve gener…
WavCube: Unifying Speech Representation for Understanding and Generation via Semantic-Acoustic Joint Modeling
Guanrou Yang, Tian Tan, Qian Chen +12
Integrating speech understanding and generation is a pivotal step toward building unified speech models. However, the different representations required for these two tasks current…
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…
FineLAP: Taming Heterogeneous Supervision for Fine-grained Language-Audio Pretraining
Xiquan Li, Xuenan Xu, Ziyang Ma +4
Contrastively pretrained audio-language models (e.g., CLAP) excel at clip-level understanding but struggle with frame-level tasks. Existing extensions fail to exploit the varying g…
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…
Resonate: Reinforcing Text-to-Audio Generation via Online Feedback from Large Audio Language Models
Xiquan Li, Junxi Liu, Wenxi Chen +3
Reinforcement Learning (RL) has become an effective paradigm for enhancing Large Language Models (LLMs) and visual generative models. However, its application in text-to-audio (TTA…
SLAM-LLM: A Modular, Open-Source Multimodal Large Language Model Framework and Best Practice for Speech, Language, Audio and Music Processing
Ziyang Ma, Guanrou Yang, Wenxi Chen +19
The recent surge in open-source Multimodal Large Language Models (MLLM) frameworks, such as LLaVA, provides a convenient kickoff for artificial intelligence developers and research…
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…
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…
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…
MeanAudio: Fast and Faithful Text-to-Audio Generation with Mean Flows
Xiquan Li, Junxi Liu, Yuzhe Liang +3
Recent years have witnessed remarkable progress in Text-to-Audio Generation (TTA), providing sound creators with powerful tools to transform inspirations into vivid audio. Yet desp…
Towards Reliable Large Audio Language Model
Ziyang Ma, Xiquan Li, Yakun Song +8
Recent advancements in large audio language models (LALMs) have demonstrated impressive results and promising prospects in universal understanding and reasoning across speech, musi…
MMAR: A Challenging Benchmark for Deep Reasoning in Speech, Audio, Music, and Their Mix
Ziyang Ma, Yinghao Ma, Yanqiao Zhu +31
We introduce MMAR, a new benchmark designed to evaluate the deep reasoning capabilities of Audio-Language Models (ALMs) across massive multi-disciplinary tasks. MMAR comprises 1,00…
Towards Flow-Matching-based TTS without Classifier-Free Guidance
Yuzhe Liang, Wenzhe Liu, Chunyu Qiang +7
Flow matching has demonstrated strong generative capabilities and has become a core component in modern Text-to-Speech (TTS) systems. To ensure high-quality speech synthesis, Class…
Enhancing Speech-to-Speech Dialogue Modeling with End-to-End Retrieval-Augmented Generation
Pengchao Feng, Ziyang Ma, Wenxi Chen +4
End-to-end speech-to-speech (S2S) dialogue systems have recently garnered increasing research attention for their lower latency and more natural integration of nonverbal cues such…
SimulS2S-LLM: Unlocking Simultaneous Inference of Speech LLMs for Speech-to-Speech Translation
Keqi Deng, Wenxi Chen, Xie Chen +1
Simultaneous speech translation (SST) outputs translations in parallel with streaming speech input, balancing translation quality and latency. While large language models (LLMs) ha…
EmoVoice: LLM-based Emotional Text-To-Speech Model with Freestyle Text Prompting
Guanrou Yang, Chen Yang, Qian Chen +12
Human speech goes beyond the mere transfer of information; it is a profound exchange of emotions and a connection between individuals. While Text-to-Speech (TTS) models have made h…
URO-Bench: Towards Comprehensive Evaluation for End-to-End Spoken Dialogue Models
Ruiqi Yan, Xiquan Li, Wenxi Chen +5
Recent advances in large language models (LLMs) have driven significant progress in end-to-end spoken dialogue models (SDMs). In contrast to text-based LLMs, the evaluation framewo…
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)…
DRCap: Decoding CLAP Latents with Retrieval-Augmented Generation for Zero-shot Audio Captioning
Xiquan Li, Wenxi Chen, Ziyang Ma +5
While automated audio captioning (AAC) has made notable progress, traditional fully supervised AAC models still face two critical challenges: the need for expensive audio-text pair…
EmoBox: Multilingual Multi-corpus Speech Emotion Recognition Toolkit and Benchmark
Ziyang Ma, Mingjie Chen, Hezhao Zhang +6
Speech emotion recognition (SER) is an important part of human-computer interaction, receiving extensive attention from both industry and academia. However, the current research fi…
EAT: Self-Supervised Pre-Training with Efficient Audio Transformer
Wenxi Chen, Yuzhe Liang, Ziyang Ma +2
Audio self-supervised learning (SSL) pre-training, which aims to learn good representations from unlabeled audio, has made remarkable progress. However, the extensive computational…