Ask Toscanini!-Architecting a Search Engine for Music Scores Beyond Metadata

被引:0
|
作者
Bahraini, Arman [1 ]
Tilevich, Eli [1 ]
机构
[1] Virginia Tech, Software Innovat Lab, Blacksburg, VA 24061 USA
关键词
music scores; information retrieval; search engine; MusicXML; symbolic information;
D O I
10.1145/3297280.3297356
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
As part of their trade, musicians continuously study and analyze music scores. Important musical tasks such as selecting repertoire require searching scores for their constituent elements. Searching collections of scores can be burdensome and cognitively taxing even for expert musicologists. Despite the promise of computing to facilitate searching over vast volumes of information, commercial search engines only operate on score metadata (e. g., composer, time period, genre, etc.). In this paper, we discuss the user requirements, design choices, and software architecture of a search engine for querying music scores beyond metadata (e. g., instrument range, key/time signature, dynamics, etc.). We also present our proof-of-concept implementation of this architecture-Ask Toscanini!-which supports a wide selection of user queries, expressed as structured text strings, against a collection of digital scores. The engine can search through any collection of scores, provided in the popular standardized MusicXML format, which is subsequently transformed into our custom search-efficient format. In addition to ensuring search efficiency, our design also renders the engine amenable for use by musicians, the majority of whom are not computing experts. The insights reported in this paper can help future research efforts in enhancing search technologies for music scores and can serve as a blueprint for creating commercial solutions in this domain.
引用
收藏
页码:796 / 803
页数:8
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