- IDyOM: Information Dynamics of Music. Sophisticated statistical modelling of musical structure developed in Pearce (2005).
- The Implication-Realisation Model. An implementation in R of the bottom-up and top-down principles of several variants of the Implication-Realisation model (Narmour, 1990). Designed to work with the output of the IDyOM model. As used in Pearce (2005, Ch. 8) and Pearce et al., (2010, NeuroImage).
- Digram Models: Lisp code for building and predicting using first and zeroth-order Markov models.
- I contributed to CLSQL, a Common Lisp interface to SQL relational databases such as MySQL and Oracle.
- I also contributed to the MIDI library for Common Lisp.
Research stimuli and empirical datasets
- Rhythm performance data from the Clapping Music Project presented and analysed in Duffy & Pearce (2018).
- Expectation and recognition memory data from the empirical investigation of artificial pitch sequence learning in Agres, Abdallah & Pearce (2018).
- 120 Hymns: from the English hymnal Hymns Ancient and Modern. Used to investigate melodic expectations in Pearce et al., (2010), Omigie et al., (2012), Omigie et al., (2013), and Hansen & Pearce (2014).
- Stimuli and responses from a study of melodic segmentation reported in Pearce et al., (2010).
- A MIDI version of Two Pages (1968): by Philip Glass. Used for information-theoretic analysis in Potter, Wiggins & Pearce (2007).
- Data and resampling sets used to test prediction performance of probabilistic models of musical structure in Pearce (2005, ch. 6) and Pearce & Wiggins (2004).