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Automatic Transcription of Flamenco Singing From Polyphonic Music Recordings

机译:从复音音乐录音中自动录制弗拉门戈歌

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Automatic note-level transcription is considered one of the most challenging tasks in music information retrieval. The specific case of flamenco singing transcription poses a particular challenge due to its complex melodic progressions, intonation inaccuracies, the use of a high degree of ornamentation, and the presence of guitar accompaniment. In this study, we explore the limitations of existing state of the art transcription systems for the case of flamenco singing and propose a specific solution for this genre: We first extract the predominant melody and apply a novel contour filtering process to eliminate segments of the pitch contour which originate from the guitar accompaniment. We formulate a set of onset detection functions based on volume and pitch characteristics to segment the resulting vocal pitch contour into discrete note events. A quantised pitch label is assigned to each note event by combining global pitch class probabilities with local pitch contour statistics. The proposed system outperforms state of the art singing transcription systems with respect to voicing accuracy, onset detection, and overall performance when evaluated on flamenco singing datasets.
机译:自动音符级转录被认为是音乐信息检索中最具挑战性的任务之一。弗拉门戈歌唱录音的特殊情况由于其复杂的旋律进行,语调不准确,使用高装饰性以及吉他伴奏而带来了特殊的挑战。在这项研究中,我们探讨了弗拉门戈歌唱情况下现有技术转录系统的局限性,并针对该类型提出了一种具体的解决方案:我们首先提取出主要的旋律,然后应用新颖的轮廓滤波过程来消除音高段轮廓来自吉他伴奏。我们根据音量和音高特性制定了一套发作检测功能,以将产生的人声音高轮廓分割为离散的音符事件。通过将整体音高类别概率与局部音高轮廓统计数据相结合,可以为每个音符事件分配一个量化的音高标签。当在弗拉门戈歌唱数据集上进行评估时,在语音准确度,发作检测和整体性能方面,拟议的系统优于最新的歌唱转录系统。

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