activity
20232026
most citedVALL-T: Decoder-Only Generative Transducer for Robust and Decoding-Controllable Text-to-Speech

10 citations · 14 across the 29 of their papers we have counts for

collaborators

33 papers

cs.CV2026

IEA: Amateur-Friendly Conversational Image Editing Agent via Three Stages of Multitask Alignment

Zichen Zhu, Yuheng Sun, Mingxuan Zhu +11

Current image editing software often hinges on fixed filters or expert tuning, leaving a gap between amateur users' intent and outcomes. Creations by generative models may contain…

cs.SD2026

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.…

eess.AS2026

Read What You Hear: Reference-Free Hypotheses Evaluation with Acoustic Discrepancy

Zhihan Li, Hankun Wang, Yiwei Guo +3

Automatic speech recognition systems commonly rely on reference transcriptions for evaluation, while reference-free approaches often depend on internal confidence estimation or aux…

eess.AS2026

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…

eess.AS2026

VISA: A Visual Information Strengthened Audio-Reasoning System for the Interspeech 2026 ARC Agent Track

Wenming Tu, Jian Gao, Yanru Huo +9

Audio reasoning requires multi-step, evidence-grounded inference over temporally dynamic and acoustically mixed signals, exceeding conventional perception tasks such as ASR or capt…

cs.SD2026

dots.tts Technical Report

Shi Lian, Changtao Li, Bohan Li +6

We present dotstts, a 2B-parameter continuous autoregressive text-to-speech (TTS) foundation model that models speech in a continuous latent space. Compared with existing contin…

eess.AS2026

A Unified and Reproducible Experimentation Framework for Speech Understanding

Jing Peng, Junhao Du, Chenghao Wang +21

Speech foundation models and Speech LLMs have advanced speech understanding, yet deployment-oriented model selection is hindered by non-comparable evaluations caused by mismatched…

eess.AS2026

OpenSTBench: Beyond Semantic Evaluation for Speech Translation

Yanjie An, Yuxiang Zhao, Yichi Zhang +5

Speech translation systems increasingly span speech-to-text translation (S2TT), speech-to-speech translation (S2ST), offline translation, and streaming generation, producing output…

cs.SD2026

X-Voice: Enabling Everyone to Speak 30 Languages via Zero-Shot Cross-Lingual Voice Cloning

Rixi Xu, Qingyu Liu, Haitao Li +10

In this paper, we present X-Voice, a 0.4B multilingual zero-shot voice cloning model that clones arbitrary voices and enables everyone to speak 30 languages. X-Voice is trained on…

cs.SD2026

RAS: a Reliability Oriented Metric for Automatic Speech Recognition

Wenbin Huang, Yuhang Qiu, Bohan Li +5

Automatic speech recognition systems often produce confident yet incorrect transcriptions under noisy or ambiguous conditions, which can be misleading for both users and downstream…

eess.AS2025

AHAMask: Reliable Task Specification for Large Audio Language Models without Instructions

Yiwei Guo, Bohan Li, Hankun Wang +4

Although current large audio language models (LALMs) extend text large language models (LLMs) with generic acoustic understanding abilities, they usually suffer from prompt sensiti…

cs.SD2025

Robust and Efficient Autoregressive Speech Synthesis with Dynamic Chunk-wise Prediction Policy

Bohan Li, Zhihan Li, Haoran Wang +5

Recently, autoregressive (AR) language models have emerged as a dominant approach in speech synthesis, offering expressive generation and scalable training. However, conventional A…

eess.AS2025

CodecSlime: Temporal Redundancy Compression of Neural Speech Codec via Dynamic Frame Rate

Hankun Wang, Yiwei Guo, Chongtian Shao +2

Neural speech codecs have been widely used in audio compression and various downstream tasks. Current mainstream codecs are fixed-frame-rate (FFR), which allocate the same number o…

eess.AS2025

VietASR: Achieving Industry-level Vietnamese ASR with 50-hour labeled data and Large-Scale Speech Pretraining

Jianheng Zhuo, Yifan Yang, Yiwen Shao +4

Automatic speech recognition (ASR) has made remarkable progress but heavily relies on large-scale labeled data, which is scarce for low-resource languages like Vietnamese. While ex…

cs.SD2025

Towards General Discrete Speech Codec for Complex Acoustic Environments: A Study of Reconstruction and Downstream Task Consistency

Haoran Wang, Guanyu Chen, Bohan Li +5

Neural speech codecs excel in reconstructing clean speech signals; however, their efficacy in complex acoustic environments and downstream signal processing tasks remains underexpl…

eess.AS2025

Unlocking Temporal Flexibility: Neural Speech Codec with Variable Frame Rate

Hanglei Zhang, Yiwei Guo, Zhihan Li +3

Most neural speech codecs achieve bitrate adjustment through intra-frame mechanisms, such as codebook dropout, at a Constant Frame Rate (CFR). However, speech segments inherently h…

cs.LG2025

Communication-Efficient Diffusion Denoising Parallelization via Reuse-then-Predict Mechanism

Kunyun Wang, Bohan Li, Kai Yu +2

Diffusion models have emerged as a powerful class of generative models across various modalities, including image, video, and audio synthesis. However, their deployment is often li…

eess.AS2025★ 1 cited

Recent Advances in Discrete Speech Tokens: A Review

Yiwei Guo, Zhihan Li, Hankun Wang +7

The rapid advancement of speech generation technologies in the era of large language models (LLMs) has established discrete speech tokens as a foundational paradigm for speech repr…

eess.AS2024

Why Do Speech Language Models Fail to Generate Semantically Coherent Outputs? A Modality Evolving Perspective

Hankun Wang, Haoran Wang, Yiwei Guo +3

Although text-based large language models exhibit human-level writing ability and remarkable intelligence, speech language models (SLMs) still struggle to generate semantically coh…

eess.AS2024

Fast and High-Quality Auto-Regressive Speech Synthesis via Speculative Decoding

Bohan Li, Hankun Wang, Situo Zhang +2

The auto-regressive architecture, like GPTs, is widely used in modern Text-to-Speech (TTS) systems. However, it incurs substantial inference time, particularly due to the challenge…

eess.AS2024

LSCodec: Low-Bitrate and Speaker-Decoupled Discrete Speech Codec

Yiwei Guo, Zhihan Li, Chenpeng Du +3

Although discrete speech tokens have exhibited strong potential for language model-based speech generation, their high bitrates and redundant timbre information restrict the develo…

eess.AS2024

vec2wav 2.0: Advancing Voice Conversion via Discrete Token Vocoders

Yiwei Guo, Zhihan Li, Junjie Li +5

We propose a new speech discrete token vocoder, vec2wav 2.0, which advances voice conversion (VC). We use discrete tokens from speech self-supervised models as the content features…

cs.SD2024

On the Effectiveness of Acoustic BPE in Decoder-Only TTS

Bohan Li, Feiyu Shen, Yiwei Guo +3

Discretizing speech into tokens and generating them by a decoder-only model have been a promising direction for text-to-speech (TTS) and spoken language modeling (SLM). To shorten…

eess.AS2024★ 2 cited

GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement

Yifan Yang, Zheshu Song, Jianheng Zhuo +13

The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…