activity
20242026
most citedDiscrete Audio Tokens: More Than a Survey!

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

eess.AS2026

ANCHOR: Autoregressive Non-intrusive Chunk-Ordered Refinement for Joint Multi-Resolution Speech Quality Modeling

Zhuoyan Tao, Jiatong Shi, Hye-jin Shim +1

While speech quality is typically assessed on complete utterances, streaming and generative systems require incremental estimation from partial audio. Existing predictors assume fu…

cs.CL2026

TRADE: Transducer-Augmented Decoder for Speech LLM

Yun Tang, Shanil Puri, Shinji Watanabe +1

Speech Large Language Models (Speech LLMs) lack a principled mechanism for streaming inference: their label-synchronous generation has no acoustic-frame alignment, making real-time…

cs.SD2025

Speech-DRAME: A Framework for Human-Aligned Benchmarks in Speech Role-Play

Jiatong Shi, Jionghao Han, Yichen Lu +6

Role-play has become a key testbed for generative models, expanding from text-only dialogue to multimodal interaction. Extending role-play to speech captures prosody, emotion, and…

cs.SD2025★ 1 cited

Discrete Audio Tokens: More Than a Survey!

Pooneh Mousavi, Gallil Maimon, Adel Moumen +18

Discrete audio tokens are compact representations that aim to preserve perceptual quality, phonetic content, and speaker characteristics while enabling efficient storage and infere…

cs.SD2024

Fusion of Discrete Representations and Self-Augmented Representations for Multilingual Automatic Speech Recognition

Shih-heng Wang, Jiatong Shi, Chien-yu Huang +2

Self-supervised learning (SSL) models have shown exceptional capabilities across various speech-processing tasks. Continuous SSL representations are effective but suffer from high…

eess.AS2024

Codec-SUPERB @ SLT 2024: A lightweight benchmark for neural audio codec models

Haibin Wu, Xuanjun Chen, Yi-Cheng Lin +13

Neural audio codec models are becoming increasingly important as they serve as tokenizers for audio, enabling efficient transmission or facilitating speech language modeling. The i…

eess.AS2024

ESPnet-Codec: Comprehensive Training and Evaluation of Neural Codecs for Audio, Music, and Speech

Jiatong Shi, Jinchuan Tian, Yihan Wu +17

Neural codecs have become crucial to recent speech and audio generation research. In addition to signal compression capabilities, discrete codecs have also been found to enhance do…