Precise pitch profile feature extraction from musical audio for key detection

The majority of pieces of music, including classical and popular music,are composed using music scales, such as keys. The key or the scale information of a piece provides important clues on its high level musical content, like harmonic and melodic context. Automatic key detection from music data can be useful for music classification, retrieval or further content analysis. Many researchers have addressed key finding from symbolically encoded music(MIDI); however, works for key detection in musical audio is still limited. Techniques for key detection from musical audio mainly consist of two steps:pitch extraction and key detection. The pitch feature typically characterizes the weights of presence of particular pitch classes in the music audio. In the existing approaches to pitch extraction, little consideration has been taken on pitch mistuning and interference of noisy percussion sounds in the audio signals, which inevitably affects the accuracy of key detection. In this paper, we present a novel technique of precise pitch profile feature extraction, which deals with pitch mistuning and noisy percussive sounds. The extracted pitch profile feature can characterize the pitch content in the signal more accurately than the previous techniques, thus lead to a higher key detection accuracy. Experiments based on classical and popular music data were conducted. The results showed that the proposed method has higher key detection accuracy than previous methods, especially for popular music with a lot of noisy drum sounds.