Extracting information from music audio

Аннотация

Music audio contains a great deal of information and emotional significance for human listeners. Machine systems that would be able to identify the listener-salient detail in music or that could predict listener judgments would be useful in many domains, from music theory to data compression to e-commerce. Here, I consider the kinds of information available in the music signal, reviewing current work in automatic music signal analysis, from the detection of individual notes to the prediction of listeners’ music preferences. While this is a vibrant research area, including an annual international evaluation, researchers are still far from a working model of how listeners experience music.