Computational musical instrument recognition and its application to content-based music information retrieval
Tetsuro Kitahara · Kyoto University Research Information Repository (Kyoto University) · 2007
The current capability of computers to recognize auditory events is severely limited when compared to human ability. Although computers can accurately recognize sounds that are sufficiently close to those trained in advance and that occur without other sounds simultaneously, they break down whenever the inputs are degraded by competing sounds. In this thesis, we address computational recognition of non-percussive musical instruments in polyphonic music. Music is a good domain for computational recognition of auditory events because multiple instruments are usually played simultaneously. The difficulty in handling music resides in the fact that signals (events to be recognized) and noises (events to be ignored) are not uniquely defined. This is the main difference from studies of speech recognition under noisy environments. Musical instrument recognition is also important from an industrial standpoint. The recent development of digital audio and network technologies has enabled us to handle a tremendous number of musical pieces and therefore efficient music information retrieval (MIR) is required. Musical instrument recognition will serve as one of the key technologies for sophisticated MIR because the