11 research outputs found

    'Warriors of the Word' -- Deciphering Lyrical Topics in Music and Their Connection to Audio Feature Dimensions Based on a Corpus of Over 100,000 Metal Songs

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    We look into the connection between the musical and lyrical content of metal music by combining automated extraction of high-level audio features and quantitative text analysis on a corpus of 124.288 song lyrics from this genre. Based on this text corpus, a topic model was first constructed using Latent Dirichlet Allocation (LDA). For a subsample of 503 songs, scores for predicting perceived musical hardness/heaviness and darkness/gloominess were extracted using audio feature models. By combining both audio feature and text analysis, we (1) offer a comprehensive overview of the lyrical topics present within the metal genre and (2) are able to establish whether or not levels of hardness and other music dimensions are associated with the occurrence of particularly harsh (and other) textual topics. Twenty typical topics were identified and projected into a topic space using multidimensional scaling (MDS). After Bonferroni correction, positive correlations were found between musical hardness and darkness and textual topics dealing with 'brutal death', 'dystopia', 'archaisms and occultism', 'religion and satanism', 'battle' and '(psychological) madness', while there is a negative associations with topics like 'personal life' and 'love and romance'.Comment: Corrected typo in abstract (subsample

    Guitar profiling technology in metal music production: public reception, capability, consequences and perspectives

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    This empirical study explores the guitar profiling technology and its consequences for metal music production. After briefly introducing this technology, the article investigates its public reception in reviews and online discussion boards to explore the subjective perspectives. A sub-sequent acoustic experiment tests the capability of the technology. The findings show that many guitar players and producers have been highly skeptical of digital amplification technology because of tonal shortcomings. However, meanwhile many musicians seem convinced of profil-ing technology due to its good sound quality that has been confirmed by the experiment too. Since for most metal music genres the sound quality of the electric guitar is very important, the creative practices and economic conditions of its production may likely be hugely affected by this technology. The article concludes by discussing the consequences of profiling technology regarding issues such as democratisation of production tools, changes in professional services, creative potentials and future applications of the technology that may radically change metal music production

    Living in a box: Understanding acoustic parameters in the NICU environment

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    BackgroundIn the last years, a significant body of scientific literature was dedicated to the noisy environment preterm-born infants experience during their admission to Neonatal Intensive Care Units (NICUs). Nonetheless, specific data on sound characteristics within and outside the incubator are missing. Therefore, this study aimed to shed light on noise level and sound characteristics within the incubator, considering the following domain: environmental noise, incubator handling, and respiratory support.MethodsThe study was performed at the Pediatric Simulation Center at the Medical University of Vienna. Evaluation of noise levels inside and outside the incubator was performed using current signal analysis libraries and toolboxes, and differences between dBA and dBSPL values for the same acoustic noises were investigated. Noise level results were furthermore classed within previously reported sound levels derived from a literature survey. In addition, sound characteristics were evaluated by means of more than 70 temporal, spectral, and modulatory timbre features.ResultsOur results show high noise levels related to various real-life situations within the NICU environment. Differences have been observed between A weighted (dBA) and unweighted (dBSPL) values for the same acoustic stimulus. Sonically, the incubator showed a dampening effect on sounds (less high frequency components, less brightness/sharpness, less roughness, and noisiness). However, a strong tonal booming component was noticeable, caused by the resonance inside the incubator cavity. Measurements and a numerical model identified a resonance of the incubator at 97 Hz and a reinforcement of the sound components in this range of up to 28 dB.ConclusionSound characteristics, the strong low-frequency incubator resonance, and levels in dBSPL should be at the forefront of both the development and promotion of incubators when helping to preserve the hearing of premature infants

    Music dimension ratings and factors dataset

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    Deciphering Lyrical Topics in Music and Their Connection to Audio Feature Dimensions Based on a Corpus of Over 100.000 Metal Songs

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    Abstract of paper 1211 presented at the Digital Humanities Conference 2019 (DH2019), Utrecht , the Netherlands 9-12 July, 2019

    Towards an Acoustic-Semantic Space of Extreme Metal Vocal Styles

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    Extreme vocal techniques typical for metal, e.g. growling or screaming, are characterized by low harmonicity and high roughness and associated with expressive dimensions like "aggressiveness" [Tsai et al., 2010]. Based on audio features, classification into broad style categories is possible [Kalbag & Lerch, 2022]. Which audio features are associated with the perception of emerging expressive techniques/stylistic devices that go beyond previously known categories remains open. Short phrases were extracted from 105 metal vocal tracks, 10 pilot-rated by subjects for pairwise similarity (45 comparisons). The resulting similarity matrix serves as basis for a perceptual similarity space computed using multidimensional scaling (MDS). In another pilot experiment, free verbal associations are collected for all 105 excerpts. Preliminary analyses reveal a three-dimensional similarity space whose first major axis represents the contrast between harmonic vs. more inharmonic/rough singing (Harmonic-to-Noise Ratio: r=0.837, p=0.005; Spectral Complexity: r=-0.959,

    Kurz und bĂŒndig : neue PrĂ€diktoren fĂŒr schnelle musikalische Erkennungsleistungen

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    Hintergrund: Bereits Ernst Mach (1873), Götz Marius (1891) und Carl Stumpf (1926) beschĂ€ftigten sich auf unterschiedlichen Wegen mit der Eingrenzung zeitlicher Minima fĂŒr die korrekte Erkennung von Klangereignissen in Sprache und Musik. Erst mit der Jahrtausendwende entstand jedoch, bedingt durch die Möglichkeiten der digitalen Audio-Bearbeitung, eine grĂ¶ĂŸere Anzahl von Studien (z.B. Schellenberg et al., 1999; Gjerdingen und Perron, 2008); Bigband et al., 2005), die anhand von Stimuli im Millisekundenbereich Grenzen von komplexeren Erkennungsleistungen aufstellten. WĂ€hrend frĂŒhe Untersuchungen vornehmlich Grundfrequenzen von Fragmenten aus Sprache und Musik untersuchten, thematisieren neuere Studien zumeist ĂŒbergeordnete und abstrakte Zielkategorien wie bestimmte StĂŒcktitel oder Genres. Neben methodischen Fehlern in der Stimulus-Auswahl und -Gestaltung dĂŒrfte dieser hohe Abstraktionsgrad allerdings zu einer eingeschrĂ€nkten VerlĂ€sslichkeit bislang aufgestellter Schwellenwerte gefĂŒhrt haben. Ziele: Das vorliegende Untersuchungsdesign nĂ€hert sich dem sog. Rapid Assessment komplexer musikalischer Elemente (Plinks) auf Ebene intra- und extramusikalischer Items. Es werden (a) geeignete Zielmerkmale jenseits des Genres vorgestellt und darauf aufbauend (b) optimale StimuluslĂ€ngen abgeleitet. Auf der Grundlage eines Online-Studiendesigns werden anschließend (c) geeignete PrĂ€diktoren fĂŒr die beobachteten Erkennungsleistungen prĂ€sentiert. Methoden: In einem Pretest (Expertenrating, n=6) wurden zunĂ€chst insgesamt 17 intra- und extramusikalische Zielvariablen (z.B. BlechblĂ€ser, Streichinstrumente, Stimme, Genre, Produktionsjahr) untersucht. Das genutzte Stimulusmaterial umfasste 330 Ausschnitte aus populĂ€ren MusikstĂŒcken von 50, 100, 200, 400 und 800 ms LĂ€nge. Es zeigte sich, dass bereits im Bereich von 100 ms hohe Übereinstimmungswerte fĂŒr einzelne Parameter auftraten (Brennan-Prediger Agreement Koeffizient von .63 bis .92 fĂŒr die Anwesenheit von u.a. Stimme, Orgel-, Glocken, BlechblĂ€ser- und StreicherklĂ€ngen sowie das Geschlecht von Stimmen). Der SĂ€ttigungsbereich der Übereinstimmungswerte liegt fĂŒr die meisten Parameter oberhalb einer StimuluslĂ€nge von 400 ms. FĂŒr die folgende Online-Studie wurde die Stimulus-Auswahl weiter eingegrenzt. Insgesamt n=517 Personen (m=187, w=327, ohne Angabe=3) im Alter von 16-76 Jahren (M=32,7, SD=12,71) nahmen an der allgemein zugĂ€nglichen Studie teil. Im Rahmen einer randomisierten Urnen-Zuweisung wurden den Teilnehmenden jeweils 12 von insgesamt 48 Klangbeispielen prĂ€sentiert. Die geforderte Bewertung der Stimuli wurde gegenĂŒber dem Pretest um 11 unipolare, crossmodale Items (z.B. "hell, harmonisch, dicht") ergĂ€nzt. Zusammenfassung: In der laufenden Auswertung der Erhebungsdaten werden den crossmodalen Items die ermittelten Erkennungsleistungen sowie Timbral Texture Features gegenĂŒbergestellt. Ziel ist die Untersuchung der Eignung psychoakustischer Maße als PrĂ€diktoren fĂŒr die Bewertung intra- und extramusikalischer Parameter. Die Studie beendet sich zum Zeitpunkt der Einreichung in der Auswertung. Die PrĂ€sentation der Ergebnisse wird fĂŒr die Jahrestagung der DGM 2017 angestrebt

    Kemper Profiling amplifier. An acoustic test of original and profile and consequences for music producing

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    Herbst J, Reuter C, Czedik-Eysenberg I, Gressel E, BrĂŒmmer B. Kemper Profiling amplifier. An acoustic test of original and profile and consequences for music producing. Metal Music Studies. Draft

    In the Blink of an Ear : A Critical Review of Very Short Musical Elements (Plinks)

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    At the turn of the millennium, several much-noticed studies on the rapid assessment of musical genres by very short excerpts ("plinks") have been published. While at first the research mostly focused on clips of popular pieces of music, the recognition of elements in the millisecond range has since been attracting growing attention in general. Although previous studies point to surprisingly short durations of exposure for above-chance genre recognition (mostly between 125 and 250 ms), interpretations of the results are ambiguous due to blurring factors. For example, varying duration thresholds for genre recognition could have been caused by coarse-meshed iterations, unstable audio-quality of sources used, unsatisfactory sample sizes, and insufficient theoretical foundation. In a pilot study, based on a selection of original stimuli used in related precedent studies, we aim to (a) identify essential spectral low-level audio features of the stimuli; (b) determine spectral cues which are obsolete for rapid assessement by means of a correlation analysis between audio features and recognition rates; (c) test for the reliability of genre recognition performance; and (d) compare the selected excerpt to other sections of the particular song (spectral matching). Spectral analyses of audio features are based on the MIR toolbox and on the software package dBSONIC. Replication of genre recognition is based on online-experiments, and the comparison between sound excerpts and the full song is being conducted by a researcher-developed software application. The work is currently under progress but first results indicate that recognition rate strongly depends on the more or less random selection of excerpts in previous studies, which might not always be representative of an entire song. In future studies, researchers should exert more control over the sound material: for instance, by selecting multiple excerpts from one song which should be controlled for the spectral fit to the whole piece
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