Phone Segmentation and Recognition through Phonological Activation Mapping
Phone segmentation and recognition are inherently related tasks, yet modern approaches typically model them separately. We argue that phonetic structure is already latent in the representations of self-supervised speech models (S3Ms), so one only needs to steer them to solve both tasks. We leverage S3M-based Phonological Activation Mapping (SPAM), which maps each S3M representation frame to a vector of phonological feature activations, such as voicing and nasality. On top of SPAM, we introduce two simple but effective lightweight, gradient-descent-free prediction heads: a recognition head and a segmentation head. Our method requires less than a minute of phonetic transcriptions, and the r...
| Authors | Shikhar Bharadwaj, Kwanghee Choi, Stephen McIntosh et al. |
|---|---|
| Primary category | eess.AS |
| Published | 10 July 2026 |
| Last updated at source | 10 October 2026 |
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