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Various methods have been proposed for detecting the onset times of musical notes in audio signals. We examine recent work on onset detection using spectral features such as the magnitude, phase and complex domain representations, and propose improvements to these methods: a weighted phase deviation function and a half-wave rectified complex difference.(More)
Organising or browsing music collections in a musically meaningful way calls for tagging the data in terms of e.g. rhythmic, melodic or harmonic aspects, among others. In some cases, such metadata can be extracted automatically from musical files; in others, a trained listener must extract it by hand. In this article, we consider a specific set of rhythmic(More)
Chord extraction from audio is a well-established music computing task, and many valid approaches have been presented in recent years that use different chord templates, smoothing techniques and musical context models. The present work shows that additional exploitation of the repetitive structure of songs can enhance chord extraction, by combining chroma(More)
The availability of large music collections calls for ways to efficiently access and explore them. We present a new approach which combines descriptors derived from audio analysis with meta-information to create different views of a collection. Such views can have a focus on timbre, rhythm, artist, style or other aspects of music. For each view the pieces(More)
We present MATCH, a toolkit for aligning audio recordings of different renditions of the same piece of music, based on an efficient implementation of a dynamic time warping algorithm. A forward path estimation algorithm constrains the alignment path so that dynamic time warping can be performed with time and space costs that are linear in the size of the(More)
A central problem in music information retrieval is finding suitable representations which enable efficient and accurate computation of musical similarity and identity. Low level audio features are ideal for calculating identity, but are of limited use for similarity measures, as many aspects of music can only be captured by considering high level features.(More)
Automatic music transcription is considered by many to be a key enabling technology in music signal processing. However, the performance of transcription systems is still significantly below that of a human expert, and accuracies reported in recent years seem to have reached a limit, although the field is still very active. In this paper we analyse(More)
In this work, a probabilistic model for multiple-instrument automatic music transcription is proposed. The model extends the shift-invariant probabilistic latent component analysis method, which is used for spectrogram factorization. Proposed extensions support the use of multiple spectral templates per pitch and per instrument source, as well as a(More)
OBJECTIVE To evaluate benefits for postnatal women of two psychologically informed interventions by health visitors. DESIGN Prospective cluster trial randomised by general practice, with 18 month follow-up. SETTING 101 general practices in Trent, England. PARTICIPANTS 2749 women allocated to intervention, 1335 to control. INTERVENTION Health(More)