发表机构
Cu Test Inc.（Cu Test公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文以伊朗古典音乐为案例，提出结合音高直方图与DTW的自动转录工作流程，采用music21库实现，可转录含tahrir等装饰音的微分音声乐，配套可视化与编辑工具，推进计算民族音乐学发展。
AI 中文摘要
本文介绍了一种用于自动转录微分音自由节奏声乐的计算工作流程，以伊朗古典音乐作为案例研究。我们的方法基于著名歌手卡里米（Karimi）的表演以及著名民族音乐学家马苏迪（Masoudieh）的基准转录结果[14]，这些内容随后被纳入IRMA音频-MIDI数据集[20]。为了准确提取旋律，我们采用了音高直方图结合动态时间规整（DTW）的方法。此外，我们引入了专门的音乐记谱法来捕捉该流派特有的复杂装饰音，尤其着重于声乐技巧tahrir。转录过程使用Python实现，借助music21库进行符号化音乐表示[5]。本研究不仅推进了计算民族音乐学领域的发展，还凸显了计算方法在保存和分析复杂音乐传统方面的潜力。该转录系统还生成音频音高轮廓与DTW对齐的MIDI表示的组合可视化，使用户能够查看表演与生成转录结果之间的对应关系。配套的可视化编辑器支持专家介入式修正生成的记谱结果。
英文摘要
This paper introduces a computational workflow for automatically transcribing microtonal, free-rhythm vocal music, with Iranian classical music as a case study. Our approach is based on performances by the renowned vocalist Karimi and ground truth transcriptions by the prominent ethnomusicologist Masoudieh [14], which were subsequently incorporated into the IRMA Audio-MIDI dataset [20]. To accurately extract melodies, we employ pitch histograms in conjunction with Dynamic Time Warping (DTW). Additionally, we introduce specialized musical notations to capture the intricate ornamentations characteristic of the genre, with particular emphasis on the vocal technique tahrir. The transcription process is implemented in Python using the music21 library for symbolic music representation [5]. This study not only advances the field of computational ethnomusicology but also highlights the potential of computational methods in preserving and analyzing complex musical traditions. The transcription system also generates a combined visualization of the audio pitch contour and the DTW-aligned MIDI representation, enabling users to inspect the correspondence between the performance and the generated transcription. A companion visual editor supports expert-in-the-loop correction of the resulting notation.
