@Article{          moss.ea2021-discovering,
    author       = {Moss, Fabian Claude and Rohrmeier, Martin},
    year         = {2021},
    title        = {Discovering Tonal Profiles with Latent Dirichlet
                   Allocation},
    abstract     = {Music analysis, in particular harmonic analysis, is
                   concerned with the way pitches are organized in pieces of
                   music, and a range of empirical applications have been
                   developed, for example, for chord recognition or key
                   finding. Naturally, these approaches rely on some
                   operationalization of the concepts they aim to
                   investigate. In this study, we take a complementary
                   approach and discover latent tonal structures in an
                   unsupervised manner. We use the topic model Latent
                   Dirichlet Allocation and apply it to a large historical
                   corpus of musical pieces from the Western classical
                   tradition. This method conceives topics as distributions
                   of pitch classes without assuming a priori that they
                   correspond to either chords, keys, or other harmonic
                   phenomena. To illustrate the generative process assumed by
                   the model, we create an artificial corpus with arbitrary
                   parameter settings and compare the sampled pieces to real
                   compositions. The results we obtain by applying the topic
                   model to the musical corpus show that the inferred topics
                   have music-theoretically meaningful interpretations. In
                   particular, topics cover contiguous segments on the line
                   of fifths and mostly correspond to diatonic sets.
                   Moreover, tracing the prominence of topics over the course
                   of music history over [Formula: see text]600 years
                   reflects changes in the ways pitch classes are employed in
                   musical compositions and reveals particularly strong
                   changes at the transition from common-practice to extended
                   tonality in the 19th century.},
    doi          = {10.1177/20592043211048827},
    isbn         = {2059204321},
    issn         = {2059-2043},
    journal      = {Music & Science},
    keywords     = {computational musicology,corpus studies,latent dirichlet
                   allocation,tonal pitch classes,tonality,topic modelling},
    mendeley-tags= {computational musicology},
    month        = {jan},
    url          = {http://journals.sagepub.com/doi/10.1177/20592043211048827},
    volume       = {4}
}

{"_id":"hsGf6sFZwwwN6bwYC","bibbaseid":"moss-rohrmeier-discoveringtonalprofileswithlatentdirichletallocation-2021","author_short":["Moss, F. C.","Rohrmeier, M."],"bibdata":{"bibtype":"article","type":"article","author":[{"propositions":[],"lastnames":["Moss"],"firstnames":["Fabian","Claude"],"suffixes":[]},{"propositions":[],"lastnames":["Rohrmeier"],"firstnames":["Martin"],"suffixes":[]}],"year":"2021","title":"Discovering Tonal Profiles with Latent Dirichlet Allocation","abstract":"Music analysis, in particular harmonic analysis, is concerned with the way pitches are organized in pieces of music, and a range of empirical applications have been developed, for example, for chord recognition or key finding. Naturally, these approaches rely on some operationalization of the concepts they aim to investigate. In this study, we take a complementary approach and discover latent tonal structures in an unsupervised manner. We use the topic model Latent Dirichlet Allocation and apply it to a large historical corpus of musical pieces from the Western classical tradition. This method conceives topics as distributions of pitch classes without assuming a priori that they correspond to either chords, keys, or other harmonic phenomena. To illustrate the generative process assumed by the model, we create an artificial corpus with arbitrary parameter settings and compare the sampled pieces to real compositions. The results we obtain by applying the topic model to the musical corpus show that the inferred topics have music-theoretically meaningful interpretations. In particular, topics cover contiguous segments on the line of fifths and mostly correspond to diatonic sets. Moreover, tracing the prominence of topics over the course of music history over [Formula: see text]600 years reflects changes in the ways pitch classes are employed in musical compositions and reveals particularly strong changes at the transition from common-practice to extended tonality in the 19th century.","doi":"10.1177/20592043211048827","isbn":"2059204321","issn":"2059-2043","journal":"Music & Science","keywords":"computational musicology,corpus studies,latent dirichlet allocation,tonal pitch classes,tonality,topic modelling","mendeley-tags":"computational musicology","month":"jan","url":"http://journals.sagepub.com/doi/10.1177/20592043211048827","volume":"4","bibtex":"@Article{ moss.ea2021-discovering,\n author = {Moss, Fabian Claude and Rohrmeier, Martin},\n year = {2021},\n title = {Discovering Tonal Profiles with Latent Dirichlet\n Allocation},\n abstract = {Music analysis, in particular harmonic analysis, is\n concerned with the way pitches are organized in pieces of\n music, and a range of empirical applications have been\n developed, for example, for chord recognition or key\n finding. Naturally, these approaches rely on some\n operationalization of the concepts they aim to\n investigate. In this study, we take a complementary\n approach and discover latent tonal structures in an\n unsupervised manner. We use the topic model Latent\n Dirichlet Allocation and apply it to a large historical\n corpus of musical pieces from the Western classical\n tradition. This method conceives topics as distributions\n of pitch classes without assuming a priori that they\n correspond to either chords, keys, or other harmonic\n phenomena. To illustrate the generative process assumed by\n the model, we create an artificial corpus with arbitrary\n parameter settings and compare the sampled pieces to real\n compositions. The results we obtain by applying the topic\n model to the musical corpus show that the inferred topics\n have music-theoretically meaningful interpretations. In\n particular, topics cover contiguous segments on the line\n of fifths and mostly correspond to diatonic sets.\n Moreover, tracing the prominence of topics over the course\n of music history over [Formula: see text]600 years\n reflects changes in the ways pitch classes are employed in\n musical compositions and reveals particularly strong\n changes at the transition from common-practice to extended\n tonality in the 19th century.},\n doi = {10.1177/20592043211048827},\n isbn = {2059204321},\n issn = {2059-2043},\n journal = {Music & Science},\n keywords = {computational musicology,corpus studies,latent dirichlet\n allocation,tonal pitch classes,tonality,topic modelling},\n mendeley-tags= {computational musicology},\n month = {jan},\n url = {http://journals.sagepub.com/doi/10.1177/20592043211048827},\n volume = {4}\n}\n\n","author_short":["Moss, F. C.","Rohrmeier, M."],"key":"moss.ea2021-discovering","id":"moss.ea2021-discovering","bibbaseid":"moss-rohrmeier-discoveringtonalprofileswithlatentdirichletallocation-2021","role":"author","urls":{"Paper":"http://journals.sagepub.com/doi/10.1177/20592043211048827"},"keyword":["computational musicology","corpus studies","latent dirichlet allocation","tonal pitch classes","tonality","topic modelling"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://hmb.sampaio.me/bibliografia.bib.txt","dataSources":["n6MFY2CscQLDpJ7nT"],"keywords":["computational musicology","corpus studies","latent dirichlet allocation","tonal pitch classes","tonality","topic modelling"],"search_terms":["discovering","tonal","profiles","latent","dirichlet","allocation","moss","rohrmeier"],"title":"Discovering Tonal Profiles with Latent Dirichlet Allocation","year":2021}