cs.SD · 2026-08-09 · No. 79

Sound, 2026-08-09.

2 new papers in cs.SD. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    Audio-to-Score Transcription using Pre-trained Features, Data Augmentation, and the New SheetSage-A2S Dataset

    Eoin Cummins, Zhongyi Huang, Alexandre D'Hooge, Zhuoro Mo, Yaolong Ju

    cs.SD · cs.AI · cs.MM

    Existing audio-to-score (A2S) systems primarily focus on classical music, and the application to popular music remains underexplored. This paper first presents the new SheetSage-A2S Dataset, which includes 61 hours of audio with \texttt{**kern} score encodings for 9,468 clips originating from 6,066 unique songs, the first of its kind to facilitate A2S research for popular music. Additionally, we improve on existing A2S approaches by using...

    arxiv.org/abs/2608.06165 · PDF

  2. 02

    LILAC: An Idempotent Neural Speech Codec

    June Young Yi, Dongwook Lee, Jiheum Yeom, Sungroh Yoon

    cs.SD · cs.LG

    Neural Audio Codecs are widely adopted in speech generation and editing. However, existing neural audio codecs are not idempotent: across the paper's twelve baseline systems, every configuration tested rewrites, on average, at least 15% of its tokens in a single decode-re-encode pass. This poses a problem for utilizing Neural Audio Codecs as token interfaces in pipelines where re-encoding decoded outputs can occur. We present LILAC, a fully...

    arxiv.org/abs/2608.05727 · PDF

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