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20242026
most citedAudio Cross Verification Using Dual Alignment Likelihood Ratio Test

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SD20261 cited

Audio Cross Verification Using Dual Alignment Likelihood Ratio Test

Heidi Lei, Arm Wonghirundacha, Irmak Bukey +1

This paper explores a way to verify that audio has not been maliciously tampered in a specific context: short viral videos taken from news recordings. Rather than trying to detect…

cs.SD2026

Local Multimodal Music Alignment from Global Supervision

Irmak Bukey, Zachary Novack, Jongmin Jung +2

Understanding music requires understanding localized relationships across data modalities, e.g., how time in performance audio maps onto position in a score image. Yet supervision…

cs.SD2026

Rethinking Music Captioning with Music Metadata LLMs

Irmak Bukey, Zhepei Wang, Chris Donahue +1

Music captioning, or the task of generating a natural language description of music, is useful for both music understanding and controllable music generation. Training captioning m…

cs.SD2025

Unified Cross-modal Translation of Score Images, Symbolic Music, and Performance Audio

Jongmin Jung, Dongmin Kim, Sihun Lee +5

Music exists in various modalities, such as score images, symbolic scores, MIDI, and audio. Translations between each modality are established as core tasks of music information re…

cs.SD2024

Just Label the Repeats for In-The-Wild Audio-to-Score Alignment

Irmak Bukey, Michael Feffer, Chris Donahue

We propose an efficient workflow for high-quality offline alignment of in-the-wild performance audio and corresponding sheet music scans (images). Recent work on audio-to-score ali…