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CASM: Context-Aware Semi-Markov Post-Processor for Beat Tracking — arXiv:2610.09318

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.09318
License (as archived): CC0-1.0
Archived: 2026-10-08T14:17:25.358Z
SHA-256 of the archived text: de2aadc8e4e25ba28cda486d4a7c3c30c16141cae280b3dd9b255289d0c8b821
Stable URL of this page: https://metraipolis.com/documento/dc_7bd8d35ecfe7

How to cite

CASM: Context-Aware Semi-Markov Post-Processor for Beat Tracking — arXiv:2610.09318 — arXiv (en), https://arxiv.org/abs/2610.09318 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_7bd8d35ecfe7 (Metraipolis archive dc_7bd8d35ecfe7, sha256 de2aadc8e4e25ba28cda486d4a7c3c30c16141cae280b3dd9b255289d0c8b821)

BibTeX

@misc{dc7bd8d35ecfe7,
  title = {CASM: Context-Aware Semi-Markov Post-Processor for Beat Tracking — arXiv:2610.09318},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.09318},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_7bd8d35ecfe7; sha256 de2aadc8e4e25ba28cda486d4a7c3c30c16141cae280b3dd9b255289d0c8b821},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.09318. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

In music beat tracking, model-predicted activations must be decoded into a discrete, musically coherent event sequence. Direct peak picking closely follows local evidence but can retain spurious peaks or miss weak beats. Dynamic Bayesian networks (DBNs), a widely used structured post-processor, improve sequence consistency under predefined global tempo, meter, and transition constraints, but their behavior can depend strongly on these settings. We introduce CASM, a context-aware semi-Markov decoder that instead conditions its temporal constraint on local activation evidence. CASM also accounts for ambiguity among competing periodic interpretations, including half- and double-tempo alternatives. Deterministic safeguards prevent implausible outputs and preserve beat-downbeat consistency. Applied to fixed activations from three neural beat trackers (BeatThis, MSCNN, and TCN), CASM improves temporal continuity while preserving event-level F1 across the GTZAN and SMC datasets, without backbone retraining or dataset-specific retuning. Further analysis shows that CASM is less sensitive than the DBN baseline to the composition of the calibration data.

Tema degli esploratori: agenti e intelligenza artificiale (elenco arXiv eess.AS, nuovi lavori del giorno).
Categorie arXiv: Audio and Speech Processing (eess.AS) ; Sound (cs.SD).
Pagina del lavoro: https://arxiv.org/abs/2610.09318 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T13:29:00.758Z dalla pagina https://arxiv.org/list/eess.AS/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).