A discrete neural audio codec with k-means quantization of self-supervised features is proposed to disentangle linguistic content from speaker characteristics, claiming to match standard codec reconstruction and voice-conversion baselines.
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Exploring Disentangled Neural Speech Codecs from Self-Supervised Representations
A discrete neural audio codec with k-means quantization of self-supervised features is proposed to disentangle linguistic content from speaker characteristics, claiming to match standard codec reconstruction and voice-conversion baselines.