{"title":"Playing technique classification for bowed string instruments from raw audio","authors":"A. Kruger, J. P. Jacobs","doi":"10.1080/09298215.2020.1784957","DOIUrl":"https://doi.org/10.1080/09298215.2020.1784957","url":null,"abstract":"Music instrument playing technique classification based on raw audio is a relatively unexplored area of music information retrieval research. This study systematically investigates the use of traditional audio features augmented by features based on the Hartley transform, used as input to a multiclass support vector machine (SVM) classifier, to identify up to 11 different playing techniques performed on each of the violin, viola, cello, and contrabass. Furthermore, 36- and 44-class joint instrument and playing technique classifiers were developed that achieved macro-average F-measures exceeding 0.88. Our approach expands and improves on the state-of-the-art study, which implemented sparse-coded magnitude and phase-derived spectral features.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1784957","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42447795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Felix Christian Thiesen, R. Kopiez, Daniel Müllensiefen, Christoph Reuter, Isabella Czedik-Eysenberg
{"title":"Duration, song section, entropy: Suggestions for a model of rapid music recognition processes","authors":"Felix Christian Thiesen, R. Kopiez, Daniel Müllensiefen, Christoph Reuter, Isabella Czedik-Eysenberg","doi":"10.1080/09298215.2020.1784955","DOIUrl":"https://doi.org/10.1080/09298215.2020.1784955","url":null,"abstract":"In an online study, N = 517 participants rated 48 very short musical stimuli comprised of well-known pop songs with regard to arrangement parameters and cross-modal variables. Identification rates for songs and artists ranged between 0-7%. We observed associations between increasing stimulus durations as well as structural sections (chorus or verse) and detection rates. Analyses of the cross-modal variables revealed a main factor, representing the perceived ‘orderliness' of a plink as a strong predictor for title recognition. When psychoacoustic low-level features were entered, Spectral Entropy became the main predictor. The presence of a singing voice additionally seemed to facilitate recognition processes.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1784955","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46745704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measurable changes in piano performance of scales and arpeggios following a Body Mapping workshop","authors":"Teri Slade, G. Comeau, D. Russell","doi":"10.1080/09298215.2020.1784958","DOIUrl":"https://doi.org/10.1080/09298215.2020.1784958","url":null,"abstract":"Body Mapping is becoming increasingly popular among musicians as an educational approach to improve bodily movement and thereby the audible quality of music performances. This study used MIDI data to quantitatively measure changes in scale and arpeggio piano performance one day before and one day after a Body Mapping workshop. While there were subtle changes in the MIDI data, these changes were generally neither statistically significant, nor a magnitude that would be audible. Based on these findings, we theorise that reports of immediate improvements to music performance originate in visual dominance: audience members observe changes in bodily movement and perceive this as improved sound quality.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1784958","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47845076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discrete Fourier transform-based method for analysis of a vibrato tone","authors":"Hee-Suk Pang, Jun-Seok Lim, Seokjin Lee","doi":"10.1080/09298215.2020.1784959","DOIUrl":"https://doi.org/10.1080/09298215.2020.1784959","url":null,"abstract":"Vibrato is one of the most common musical techniques used for the enrichment of vocal and musical instrument sounds. We propose a method that can analyse the intonation, vibrato rate, and vibrato extent of a vibrato tone as a function of time, which is based on the discrete Fourier transform of its fundamental frequency trajectory. According to experimental results, the proposed method is robust to the irregularities in the fundamental frequency trajectory. In addition, the proposed method provides different results for intonation and vibrato extent from those of Prame’s method when the fundamental frequency trajectory is not perfectly sinusoidal.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1784959","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45539528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Redefining sad music: Music’s structure suggests at least two sad states","authors":"L. Warrenburg","doi":"10.1080/09298215.2020.1784956","DOIUrl":"https://doi.org/10.1080/09298215.2020.1784956","url":null,"abstract":"Many researchers have noted inconsistencies between descriptions and effects of nominally sad music. The current study addresses whether traditional music-related sadness can be broken down into more than one category. Melancholic and grieving musical passages were collected in three stages. Participants with superior aural skills rated 18 structural parameters of these musical passages on 7-point unipolar scales. The results are consistent with the idea that musical parameters differ in melancholic and grieving states and that what has been previously defined as sad music may, in fact, be conflating more than one emotional state.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1784956","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46512575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Steffen Lepa, Martin Herzog, J. Steffens, Andreas Schoenrock, Hauke Egermann
{"title":"A computational model for predicting perceived musical expression in branding scenarios","authors":"Steffen Lepa, Martin Herzog, J. Steffens, Andreas Schoenrock, Hauke Egermann","doi":"10.1080/09298215.2020.1778041","DOIUrl":"https://doi.org/10.1080/09298215.2020.1778041","url":null,"abstract":"We describe the development of a computational model predicting listener-perceived expressions of music in branding contexts. Representative ground truth from multi-national online listening experiments was combined with machine learning of music branding expert knowledge, and audio signal analysis toolbox outputs. A mixture of random forest and traditional regression models is able to predict average ratings of perceived brand image on four dimensions. Resulting cross-validated prediction accuracy (R²) was Arousal: 61%, Valence: 44%, Authenticity: 55%, and Timeliness: 74%. Audio descriptors for rhythm, instrumentation, and musical style contributed most. Adaptive sub-models for different marketing target groups further increase prediction accuracy.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1778041","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44537978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Effect of tempo on relative note durations in a performed samba groove","authors":"Mari Romarheim Haugen, A. Danielsen","doi":"10.1080/09298215.2020.1767655","DOIUrl":"https://doi.org/10.1080/09298215.2020.1767655","url":null,"abstract":"Previous studies have revealed uneven duration patterns at the sixteenth note level of samba. In the present study, we investigated the influence of tempo on such sixteenth-note patterns in a performed samba groove.The results revealed an uneven duration pattern in all tempi. Interestingly, the shortest note becomes relatively shorter and the longest relatively longer as the tempo increases. We suggest that the differences in relative durations between tempi reflect the need to maintain the samba sixteenth note ‘template’ in all tempi: producing the samba ‘feel’ requires that relative durations have to be adjusted to tempo.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1767655","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49439412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Gusev, I. V. Bakhmutova, L. A. Miroshnichenko, T. N. Titkova
{"title":"Possible approaches to deciphering Russian ancient Znamenny chant","authors":"V. Gusev, I. V. Bakhmutova, L. A. Miroshnichenko, T. N. Titkova","doi":"10.1080/09298215.2020.1762666","DOIUrl":"https://doi.org/10.1080/09298215.2020.1762666","url":null,"abstract":"In this article we provide approaches to translating into modern music notation Znamenny Russian Church chants, written in neumatic (“znamenny” or “hook”) notation. Neumes are sequences of notes of varying lengths, that correspond to singing one syllable of old Slavonic verse. Starting in 17th century, neumes were supplemented with pomjeta facilitating mapping into modern music notation. Manuscripts from earlier periods have no pomjeta and are thus not readable today. This paper introduces computer-based approaches to the reconstruction of znamenny notation without pomjeta into modern music notation. These approaches are trained on dvojyeznamenniks but can be applied to manuscripts without pomjeta.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1762666","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46109398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antonio Caparrini, J. Arroyo, Laura Pérez-Molina, J. Sánchez-Hernández
{"title":"Automatic subgenre classification in an electronic dance music taxonomy","authors":"Antonio Caparrini, J. Arroyo, Laura Pérez-Molina, J. Sánchez-Hernández","doi":"10.1080/09298215.2020.1761399","DOIUrl":"https://doi.org/10.1080/09298215.2020.1761399","url":null,"abstract":"Electronic dance music (EDM) is a genre where thousands of new songs are released every week. The list of EDM subgenres considered is long, but it also evolves according to trends and musical tastes. With this in view, we have retrieved two sets of over 2000 songs separated by more than a year. Songs belong to the top 100 list of an EDM website taxonomy of more than 20 subgenres that changed in the period considered. We test the effectiveness of automatic classification on these sets and delve into the results to determine, for example, which subgenres perform better and worse, how the performance of some subgenres change in the two sets, or how some subgenres are often confused with one another. We illustrate confusion among subgenres by a graph and interpret it as a taxonomic map of EDM. We also assess the deterioration of the performance of the classifier of the first set when used to classify the second one. Finally, we study how the new subgenres that appear in the second set relate to the old ones with the help of the classifier of the first set. As a result, this work illustrates the main challenges that EDM poses to automatic classification and provides insights into where are the limits of this approach.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1761399","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"59858216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Rhythmic variability, language, and style: A replication and extension of nPVI findings with the RISM dataset","authors":"Katherine Vukovics, D. Shanahan","doi":"10.1080/09298215.2020.1751209","DOIUrl":"https://doi.org/10.1080/09298215.2020.1751209","url":null,"abstract":"The normalised pairwise variability index (nPVI), has been frequently used to measure the rhythmic variance between musical onsets. For example, researchers have proposed connections between the nationalities of composers and the nPVI values of their music and native language. One particular issue, however, lies in the notion of intended nationality – composers frequently wrote in national styles other than their own. This study employs the RISM-World dataset to both replicate previous findings relating the rhythmic variance of melodies to the nationalities of composers, and to examine intended nationality in the music of Mozart and Handel, namely their operas and oratorios.","PeriodicalId":16553,"journal":{"name":"Journal of New Music Research","volume":null,"pages":null},"PeriodicalIF":1.1,"publicationDate":"2020-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09298215.2020.1751209","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42940984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}