複音音樂之音高辨識

Pitch Detection for Polyphonic Music

王炳堯(Ping-Yao Wang)

指導教授 ： 鄭士康

國立臺灣大學/電機資訊學院/電機工程學研究所/碩士(2008年)

https://doi.org/10.6342/NTU.2008.02849

摘要

音樂自動採譜近來在電腦音樂領域是一個熱門的研究主題。然而因不同音高的訊號混合受到了相位差的影響，因此難以正確使用簡單方法來正確辨識複音音樂的音高。在這篇論文中，我們提出了一個解決複音音樂之音高辨識問題的方法。我們專注於將不同音高訊號中相同頻率的泛音成份從輸入訊號中分離出來。藉由預先建立的可提供合理泛音成份組成參考的樂器音色參數機率模型，我們使用全域最佳化方法來找出最符合輸入訊號的最佳參數，藉以得到音樂訊號中的音高。從評估我們提出的方法以及其他方法的過程，可以證明我們所提出方法在準確率以及強固性所帶來的進步。

關鍵字

複音音樂 ； 音高辨識 ； 自動採譜 ； 標型辨識 ； 全域最佳化

並列摘要

Music transcription is a popular research topic recently. However, estimating pitch in polyphonic music signal encounters difficulties since the signal is a mixture of waveforms from all notes with phase differences, and estimation errors can easily arise when simple greedy methods are used. In this thesis, we propose a method to solve the problem of estimating the pitches in polyphonic music. We try to focus on separating the harmonic components of the same frequency from different notes from the observed mixtures in the music signal. With the pre-built probabilistic model of instrument timbre, which provides a reference for the reasonable ratio of each harmonic component in a pitched note, we use global optimization method to estimate optimal parameters to separate each note from the music signal. Two types of evaluation, including pitch estimation on note combinations of different intervals and pitch estimation on short music pieces, was done on the proposed system and other methods, which shows the performance and robustness of the proposed method.

並列關鍵字

Polyphonic Music ； Pitch Estimation ； Automatic Music Transcription ； Pattern Recognition ； Global Optimization

參考文獻

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