Separation of musical sources and structure from single-channel polyphonic recordings

The thesis deals principally with the separation of pitched sources from singlechannel polyphonic musical recordings. The aim is to extract from a mixture a set of pitched instruments or sources, where each source contains a set of similarly sounding events or notes, and each note is seen as comprising partial, transient and noise content. The work also has implications for separating nonpitched or percussive sounds from recordings, and in general, for unsupervised clustering of a list of detected audio events in a recording into a meaningful set of source classes. The alignment of a symbolic score/MIDI representation with the recording constitutes a pre-processing stage. The three main areas of contribution are: firstly, the design of harmonic tracking algorithms and spectralfiltering techniques for removing harmonics from the mixture, where particular attention has been paid to the case of harmonics which are overlapping in frequency. Secondly, some studies will be presented for separating transient attacks from recordings, both when they are distinguishable from and when they are overlapping in time with other transients. This section also includes a method which proposes that the behaviours of the harmonic and noise components of a note are partially correlated. This is used to share the noise component of a mixture of pitched notes between the interfering sources. Thirdly, unsupervised clustering has been applied to the task of grouping a set of separated notes from the recording into sources, where notes belonging to the same source ideally have similar features or attributes. Issues relating to feature computation, feature selection, dimensionality and dependence on a symbolic music representation are explored. Applications of this work exist in audio spatialisation, audio restoration, music content description, effects processing and elsewhere.