AI & ML
A Learned Musical-Time Coordinate for Piano Audio-to-Score Transcription
arXiv cs.SD0 views
arXiv:2610.29928v1 Announce Type: new Abstract: End-to-end piano audio-to-score (A2S) transcription is the task of reconstructing a notated score from an audio recording in a single system. Existing A2S approaches usually rely on pre-segmented excerpts, and few handle whole pieces without external segmentation. This raises the question of whether a musical-time coordinate can guide score transcription while also helping the system segment whole pieces. Previous work on jazz saxophone A2S uses an external beat tracker to obtain such a coordinate for score prediction. We introduce downbeat phase, a musical-time coordinate learned jointly with score transcription that represents each audio frame's relative position within a notated bar. With this coordinate, our system can not only condition its score decoder on downbeat phase but also self-segment at bar boundaries and stitch the segments into a whole piece. Evaluation suggests that the coordinate improves metrical structure and supports whole-piece transcription with comparable notation quality.
Source:https://arxiv.org/abs/2610.29928PreviousAT-Differ: Dataset for Audio-Text Difference CaptioningNextHow Far Can the Gemma 4 Speech Encoder Go Without Changing Its Weights? Saudi and Gulf Arabic Speech Recognition with a Frozen and an Adapter-Augmented Encoder
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