| Summary: | 碩士 === 國立成功大學 === 資訊工程學系 === 104 === Dated back to the 40’s, Jazz ensembles such as trios, quartets or even quintets became popular. Miles Davis kept the flame for more than 20 years. In this period, jazz masters, like Thelonious Monk, John Coltrane, Sonny Rollins, Bill Evans, built their own ensembles. The number of commercial recordings is so large and they are all treasures of human music history.
The key persons of jazz ensembles are usually wind or piano players. Free style improvisation characterizes such a music genre, though drummers and bassists are still the ones who sustain foundation of musical performances. Unlike most pop music, they often neither employ consistent playing patterns nor keep constant tempo throughout the performance because improvisation is their soul. In the meanwhile, they have to hold all the players together. As a matter of fact, rhythmic instrument players are as important as the soloists. That is why drummers and bassists, such as Ray Brown and Max Roach, are remembered as masters too.
There are quite a few algorithms focusing on rhythmic instrument performance analysis. Very few of them are designed for the analysis of recordings of jazz ensembles. It is found that these algorithms aren’t as effective for our target recordings, mostly well under 70%.
In response to the difficulties discussed above, the sounds of rhythmic instruments of jazz quartet can be divided into two types. The first type has clear harmonic structures such as that produced by a contrabass. The second type possesses broadband characteristics such as sounds produced by hi-hat cymbal and snare drum. We trained multi-HMM (Hidden Markov Model) in training stage, and extracting onsets of rhythmic instruments using these HMMs with pre-processing, and then focus on the onsets to recognize the instruments with their respective characteristics.
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