Zhao et al.
Marginal utility allocation of audio tokens improves quality under strict bit budgets
UniAdapt learns where RVQ refinements are most valuable, reducing distortion across speech, music and environmental audio without increasing bitrate.
Chinese Tech
Mingyu Zhao · Jinchao Zhang · Zhiyong Wu
Tsinghua University · Tencent
Research Digest··2 min read
The authors introduce UniAdapt, a method that learns the marginal utility of residual-vector-quantization (RVQ) refinements on a frozen codec and allocates tokens under exact serialized-bit budgets.
Why this paper
From Tencent and Tsinghua University
In one line
UniAdapt learns marginal utility of RVQ refinements to allocate variable depths under fixed bit budgets, reducing distortion without increasing bitrate.
What we could check
- ·No code link found
- ·No weights link found
- ·No dataset link found
- ·No compute details found
- ·No stated limitations found
- ✓Reports numbers on named benchmarks (2 benchmarks)
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