Computational Analysis of Musical Influence: a Musicological Case Study Using Mir Tools
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11th International Society for Music Information Retrieval Conference (ISMIR 2010) COMPUTATIONAL ANALYSIS OF MUSICAL INFLUENCE: A MUSICOLOGICAL CASE STUDY USING MIR TOOLS Nick Collins Department of Informatics, University of Sussex, Falmer, Brighton, BN1 9QJ, UK [email protected] ABSTRACT of genres is implicit in much discussion of the philosophy of stylistic categories in music [1, 10], and related to sim- Are there new insights through computational methods to ilar questions in biology concerning speciation events and the thorny problem of plotting the flow of musical influ- memetics [4, 6]. ence? This project, motivated by a musicological study of Automated methods for the analysis of musical similar- early synth pop, applies MIR tools as an aid to the inves- ity provide a new angle on relationships between works, tigator. Web scraping and web services provide one an- whether comparing individual pieces or within larger cor- gle, sourcing data from allmusic.com, and utilising python pora. For example, the data-driven analyses explored by APIs for last.fm, EchoNest, and MusicBrainz. Charts of David Cope across MIDI files [3] are primarily used for influence are constructed in GraphViz combining artist sim- synthesis, but can also help to explore the links between ilarity and dates. Content based music similarity is the sec- composers. Symbolic analysis tools in MIR parallel such ond approach, based around a core collection of synth pop movements in algorithmic composition: McKay and Fu- albums. The prospect for new musical analyses are dis- jinaga [11] discuss the application of their jSymbolic fea- cussed with respect to these techniques. ture extractor and Autonomous Classification Engine ma- chine learning tool to such projects as comparison between a Chopin nocturne and Mendelssohn piano trio, or distin- 1. INTRODUCTION guishing de Machaut and Palestrina. Charles Smith has Musicians have always been aware of issues of musical in- carried out perhaps the largest musicological study of in- fluence, from the lists of influences set out in adverts for fluence amongst classical composers by a series of mea- new band members, the intensive relationship of teachers sures applied over library resources, and presents it in a and pupils in many traditions, to composers consciously website describing the ‘Classical Music Universe’. 1 admitting their predecessors through interviews, personal There are many MIR studies which have analyzed the journals, and in some cases unconscious or deliberate quo- current state of public opinion on artist similarity, for pur- tations. Whilst it is convenient to focus on grand examples poses of tracking popularity and making recommendations. in a ‘genius’ model of musical history, all eras of music Zadel and Fujinaga [19] combine cultural meta-data from have had a host of active musicians, though no era more Amazon with a metric of similarity based on Google search than today’s hyper-warren of content creators. Chopin’s counts to generate a network of related artists through web letters, for example, are littered with references to other services. Fields et al. [8] scraped MySpace pages, trac- active pianist-composers of the day, most of whom are no ing the recursive (to sixth degree of separation) network longer household names, yet Chopin writes ‘I shall not be of friends and evaluating musical similarity through audio an imitation of Kalkbrenner: he has not the power to extin- content analysis of their sound examples. They mention guish my perhaps too audacious but noble wish and inten- influence as one potential link between artists, but do not tion to create for myself a new world’ [9, p. 103]. The unpack it from collaboration or general similarity. Park et literature on human creativity is of note here in explor- al. [13] also study the network structure of artists, by scrap- ing the processes of human invention within the engine of ing online music databases such as allmusic.com, but con- culture [5, 15]. Musicologists have re-cast traditional con- centrate on collaboration or ‘expert’ annotated similarity cerns over influence to questions of ‘inter-textuality’, and rather than any explicit tie to dates. Again tackling MyS- the degree to which any musical work can be seen as dis- pace, Beuscart and Couronne´ [2] namecheck influence in tinct from social and musical currents [16]. Influence is their title, but mean it as a general measure of recommen- intimately connected to the continuous negotiation of mu- dation amongst cliques of artists rather than as a formative sical style as it transforms over time; the gradual formation influence on creative output. Thus, although the topics of similarity and genre remain Permission to make digital or hard copies of all or part of this work for central tenets of much music information retrieval work, personal or classroom use is granted without fee provided that copies are the role of dates as markers of the flow of influence is not not made or distributed for profit or commercial advantage and that copies so widely discussed. This paper makes dates a central part bear this notice and the full citation on the first page. of a musicological investigation. The applicability of MIR c 2010 International Society for Music Information Retrieval. 1 http://people.wku.edu/charles.smith/music/index2.htm 177 11th International Society for Music Information Retrieval Conference (ISMIR 2010) tools to studies of influence both via online meta-data pars- tended careers. 3 In another example of the complications, ing and content based analysis applications is explored. In as bands progress through multiple albums, they work with the latter content analysis, a tight knit set of synth pop al- many people, often bringing in younger producers who bums from the years 1977-1981 are put under the micro- emerged in historically later scenes (in DM’s case, such scope, providing a real challenge for discrimination and a as Flood, or Mark Bell). The network of musicians who microcosm of gradual stylistic change. influenced, and who were influenced by, Depeche Mode Section 2 introduces the context of synth pop as well as are examined in a web data analysis, and work historically the central node, Depeche Mode (DM). Section 3 presents closely prior to the album Speak & Spell is the focus for web scraping and web service exploration of the network the audio content analysis. of artists around DM, with a technique to automatically Statements by band members past and present provide extract dates for artists using the MusicBrainz web ser- insight into the formative influences of the band. For ex- vice. Network diagrams are constructed through python ample, in Miller’s biography [12], the band admit early programs and GraphViz. Section 4 tackles the influence influences including Gary Numan (p.21), OMD and the question using a set of synth pop albums from the era up track ‘Almost’ (p.23), The Human League and particularly to four years before the first DM release, looking for au- ‘Being Boiled’ (p.483), Kraftwerk (p.25) and John Foxx tomatic recognition of possible leads on influence through (p.26). DM gigged early on with the post-Foxx incarnation musical similarity (marsyas is the tool of choice here). Re- of Ultravox, and their label owner and first producer was sults and future extensions are discussed. the British DIY synth pioneer Daniel Miller; Mute Records artists would remain a central touchpoint as the band devel- 2. SYNTH POP AND DEPECHE MODE oped. Such references are further discussed below. The cost of analog synthesizers decreased in the 1970s, 3. WEB SCRAPING AND WEB SERVICES FOR until an all synthesizer band was a viable proposition for THE ANALYSIS OF INFLUENCE musicians starting out in the post punk era [14]. Although there are always earlier precedents, and synths had been Although a musicologist might construct their own model long known in popular music through such phenomena as of musical influence from analyzing primary and secondary mass selling Moog albums, prog rock keyboardists, and sources such as original releases, reviews and interviews, krautrock, a real concentration of synth led bands emerged the wealth of online commentary and databases provides a in the later 1970s into a position of mainstream chart suc- further strand of evidence for systematic musicology to ex- cess. The Second Invasion of the US by British bands ploit. Although there can be issues with the verifiability of on the back of MTV featured a plethora of synthesized information, the much remarked problems of reliability of sounds, and the 1980s saw even greater availability of elec- meta-data in MIR [7], it can still be healthy to admit web tronic equipment as digital technology stole the show. Al- content as part of the arsenal of the musicologist. This pa- though some ‘New Romatic’ bands such as Duran Duran per examines the use of web scraping and web services to had only a single keyboardist, the more central examples collect alternative viewpoints on the influences upon and of synth pop tend to feature all synthesizer backing, in- influence of a particular central band. Although the tech- cluding sequencers and drum machine in place of acoustic niques may be applied to any starting point, Depeche Mode drummers, after the Kraftwerk model; but like all supposed are chosen in particular for this study. categories, inbetween cases exist. The following APIs and websites were investigated: Depeche Mode were by no means the first synth pop band, nor the first with popular market appeal; both Kraftwerk • allmusic.com artist information explicitly contains as an all electronic band, and Gary Numan as an individ- entries for ‘Influenced By’ and ‘Followers’ ual who featured synthesizers, had had greater commercial • The EchoNest API has convenience methods to ob- success than their first album was to achieve.