ABSTRACT
Musical events are ordered according to a specific temporal sequence. Time series analysis deals with observations that are indexed by an ordered variable (usuallly time). It is therefore not surprising that time series analysis is important for analyzing musical data. Traditional applications are concerned with “raw physical data” in the form of audio signals (e.g. digital CD-recording, sound analysis, frequency recognition, synthetic sounds, modeling musical instruments). In the last few years, time series models have been developed for modeling symbolic musical data and analyzing “higher level” structures in musical performance and composition. A few examples are discussed in this chapter.
