CleanCodec reframes audio tokenization as a selective information bottleneck to encode only perceptually important features at 12.5 tokens per second, outperforming prior codecs in efficiency, speaker similarity, and intelligibility.
InICASSP 2021-2021 IEEE International Conference on Acous- tics, Speech and Signal Processing (ICASSP), pages 606–610
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HyPeR is a hybrid perception-reasoning framework that uses a new hierarchical PAQA dataset and PAUSE tokens to improve large audio language models' handling of multi-speaker and ambiguous audio.
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CleanCodec: Efficient and Robust Speech Tokenization via Perceptually Guided Encoding
CleanCodec reframes audio tokenization as a selective information bottleneck to encode only perceptually important features at 12.5 tokens per second, outperforming prior codecs in efficiency, speaker similarity, and intelligibility.
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Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding
HyPeR is a hybrid perception-reasoning framework that uses a new hierarchical PAQA dataset and PAUSE tokens to improve large audio language models' handling of multi-speaker and ambiguous audio.