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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…
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…