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20232026
most citedSeed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition

6 citations · 11 across the 8 of their papers we have counts for

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eess.AS2026

GROW: Group-Relative Advantage-Weighted On-Policy Reinforcement Learning of Autoregressive-Diffusion Text-to-Speech model

Guanrou Yang, Tian Tan, Qian Chen +8

Reinforcement learning for flow-matching text-to-speech is complicated by deterministic ODE sampling: trajectory-level policy-gradient methods typically convert the ODE into an SDE…

eess.AS2026

AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following

Haitao Li, Tian Tan, Yuguang Yang +2

The rapid advancement of instruction-guided audio generation has highlighted the critical need for robust alignment evaluation. Current automated evaluation methods heavily rely on…

eess.AS2026

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…

eess.AS20246 cited

Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition

Ye Bai, Jingping Chen, Jitong Chen +52

Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…

eess.AS20235 cited

Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models

Guangzhi Sun, Wenyi Yu, Changli Tang +6

Audio-visual large language models (LLM) have drawn significant attention, yet the fine-grained combination of both input streams is rather under-explored, which is challenging but…