6 citations · 7 across the 13 of their papers we have counts for
17 papers
SURE-EVAL: A Systematic and Unified Agentic Framework for Reproducible Evaluation
Jing Peng, Junhao Du, Yixuan Wang +21
Audio and speech models are released rapidly, but reported scores often conflate model capability with deployment and evaluation choices. The same checkpoint can produce different…
dots.tts.edit: Precisely Controlled Speech Editing with a Continuous Autoregressive Model
Hankun Wang, Bohan Li, Shi Lian +7
Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language provides a flexible interface fo…
TokAN: Accent Normalization Using Self-Supervised Speech Tokens
Qibing Bai, Shuai Wang, Yuhan Du +3
Accent normalization (AN) seeks to convert non-native (L2) accented speech into standard (L1) speech while preserving speaker identity. The current techniques either require natura…
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…
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…
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…
BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio Reconstruction
Haoran Wang, Jiatong Shi, Jinchuan Tian +3
Neural audio codecs have recently enabled high-fidelity reconstruction at high compression rates, especially for speech. However, speech and non-speech audio exhibit fundamentally…
ISA-Bench: Benchmarking Instruction Sensitivity for Large Audio Language Models
Bohan Li, Wenbin Huang, Yuhang Qiu +7
Large Audio Language Models (LALMs), which couple acoustic perception with large language models (LLMs) to extract and understand diverse information from audio, have attracted int…
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…
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…
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…
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…
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…
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…
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…
A Survey on Speech Large Language Models for Understanding
Jing Peng, Yucheng Wang, Bohan Li +9
Speech understanding is essential for interpreting the diverse forms of information embedded in spoken language, including linguistic, paralinguistic, and non-linguistic cues that…
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…