Content-Based Music Retrieval of Irish Traditional Music Via a Virtual Tin Whistle

We present a mobilephon eapplication associating a virtual musical instrument (emulating a tin whistle) to a content based music retrieval system for Irish Traditional Music (ITM). It performs tune recognition, following the architecture of the existing query-by-playing software Tunepal (Duggan & O’Shea, 2011). After explaining the motivation for this project in Section 2 and presenting some relatedworkinSection3,wedescribeourproposedapplicationinSection4. Section5discussescurrentshortcomings of our project and potential future directions

Tunepal: Searching a Digital Library of Traditional Music Scores

Purpose – This paper aims to describe the Tunepal project as an example of a music information retrieval (MIR) system that is having an impact on how musicians access, learn and play traditional Irish music around the world. Design/methodology/approach – This paper describes the functionality of the Tunepal system: consisting of the tune corpus, the web site tunepal.org and mobile apps supporting iOS and Android OS. Tunepal facilitates query-by-title and query-by-playing music (QBP) searches and allows a musician to retrieve and playback scores amongst other supported functions. Findings – Tunepal has been favorably received and musicians report that the system is being used in a variety of scenarios including archiving and the preparation of sleeve notes for commercial recordings. Tunepal has a growing user base in 25 countries. Originality/value – The comprehensive tune corpus (over 16,000 compositions), the query-by-playing technology and the fact that the mobile apps provide access to the corpus in situ in traditional music sessions and classes make this project uniquely useful

Tunepal: searching a digital library of traditional music scores

Purpose – This paper aims to describe the Tunepal project as an example of a music information retrieval (MIR) system that is having an impact on how musicians access, learn and play traditional Irish music around the world. Design/methodology/approach – This paper describes the functionality of the Tunepal system: consisting of the tune corpus, the web site tunepal.org and mobile apps supporting iOS and Android OS. Tunepal facilitates query-by-title and query-by-playing music (QBP) searches and allows a musician to retrieve and playback scores amongst other supported functions. Findings – Tunepal has been favorably received and musicians report that the system is being used in a variety of scenarios including archiving and the preparation of sleeve notes for commercial recordings. Tunepal has a growing user base in 25 countries. Originality/value – The comprehensive tune corpus (over 16,000 compositions), the query-by-playing technology and the fact that the mobile apps provide access to the corpus in situ in traditional music sessions and classes make this project uniquely useful

Compensating for expressiveness in queries to a content based music information retrieval system

MATT2 is a content based music information retrieval system adapted to the characteristics of traditional Irish dance music. MATT2 compensates for expressive artefacts commonly employed by traditional musicians. Specifically these are ornamentation, "the long note", reversing and phrasing. In this paper we describe the main components of MATT2 and present an experiment where we demonstrate that using this higher level knowledge of melodic similarity in traditional Irish dance music results in a significant improvement in annotation accuracy over standard approaches from the MIR literature

Machine Annotation of Traditional Irish Dance Music

The work presented in this thesis is validated in experiments using 130 realworld field recordings of traditional music from sessions, classes, concerts and commercial recordings. Test audio includes solo and ensemble playing on a variety of instruments recorded in real-world settings such as noisy public sessions. Results are reported using standard measures from the field of information retrieval (IR) including accuracy, error, precision and recall and the system is compared to alternative approaches for CBMIR common in the literature