SEER’s preprint describes choosing same-emotion speech references for emotional voice conversion, then evaluating outputs through cochlear-implant simulation.
Not requiring intensity labels does not mean no emotion supervision. The methods use emotion annotations when available and an auxiliary emotion classifier.
The authors form a reference bank from recordings that a pretrained speech-emotion classifier labels correctly before and after simulation. The retriever keeps the source speech when no candidate has positive predicted utility.
Those experimental rules alone do not establish emotional-hearing benefit for implant users. The conclusion places CI-listener rewards in future work.
Version one was submitted October 8, 2026; its feed announcement is October 9. Experiment years and exact first public posting remain unknown.
Source: Hsing-Hang Chou, Yun-Shao Lin, Ching-Chin Sung and Chi-Chun Lee. SEER: Source-Conditioned Emotion Enhancement via Retrieval for Cochlear-Implant Speech, arXiv2610.11131v1.
Separate intensity-label requirements from emotion supervision.
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Preprint and submission history ↗Declared manuscript PDF ↗This methods explainer describes public reference records. It does not establish study results, a product’s current authorization or treatment suitability.
