Abstract
The C@merata task at MediaEval started in 2014 and is now in its fourth year. It is a combination of Natural Language Processing and Music Information Retrieval. The input is a short query (six consecutive sixths in the right hand in bars 1-25) against a classical music score in MusicXML. The required output is a set of matching passages in the score. There are 200 queries and 20 scores each year. There were several innovations for 2017: First, some queries such as cadences required an answer which was a point in a score rather than a passage; second, queries were contributed by participants as well as by the organisers; third, some of the queries were directly taken from real texts such as articles and webpages; fourth, the organisers provided experimental representations of the input queries in the form of JSON feature structures. These capture many aspects of the queries in a form which is much closer to an MIR query. There were just two participants in the evaluation, and scores were understandably low given the considerable difficulty of the queries. However, this year we have significantly advanced our knowledge of how music is talked about in natural language texts, how these relate to MIR queries, and how to go about converting a text into a query.
Original language | English |
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Journal | CEUR Workshop Proceedings |
Volume | 1984 |
Publication status | Published - 2017 |
Externally published | Yes |
Event | 2017 Multimedia Benchmark Workshop, MediaEval 2017 - Dublin, Ireland Duration: 13 Sep 2017 → 15 Sep 2017 |