Research

Full Bibliography

108 sources from 8 research domains are cited by MusicMind's 13-layer cognitive analysis engine. Every algorithm has a citation. Every citation has a paper.

Harmony

28 sources

  1. Krumhansl, C. L. (1990). Cognitive Foundations of Musical Pitch. Oxford University Press.
  2. Lerdahl, F. (2001). Tonal Pitch Space. Oxford University Press.
  3. Lerdahl, F., & Jackendoff, R. (1983). A Generative Theory of Tonal Music. MIT Press.
  4. Lerdahl, F., & Krumhansl, C. L. (2007). Modeling tonal tension. Music Perception, 24(4), 329–366.DOI
  5. De Clercq, T., & Temperley, D. (2011). A corpus analysis of rock harmony. Popular Music, 30(1), 47–70.DOI
  6. Rohrmeier, M. (2011). Towards a generative syntax of tonal harmony. Journal of Mathematics and Music, 5(1), 35–53.DOI
  7. Steedman, M. J. (1984). A generative grammar for jazz chord sequences. Music Perception, 2(1), 52–77.DOI
  8. Cohn, R. (1998). Introduction to neo-Riemannian theory: A survey and a historical perspective. Journal of Music Theory, 42(2), 167–180.DOI
  9. Cohn, R. (2012). Audacious Euphony: Chromatic Harmony and the Triad's Second Nature. Oxford University Press.
  10. Tymoczko, D. (2004). Scale networks and Debussy. Journal of Music Theory, 48(2), 219–294.DOI
  11. Tymoczko, D. (2011). A Geometry of Music: Harmony and Counterpoint in the Extended Common Practice. Oxford University Press.
  12. Woolhouse, M. (2009). Modelling tonal attraction between adjacent musical elements. Journal of New Music Research, 38(4), 357–379.DOI
  13. Kopp, D. (2002). Chromatic Transformations in Nineteenth-Century Music. Cambridge University Press.
  14. Riemann, H. (1893). Vereinfachte Harmonielehre, oder die Lehre von den tonalen Funktionen der Akkorde. Augener.
  15. Harrison, D. (1994). Harmonic Function in Chromatic Music: A Renewed Dualist Theory and an Account of Its Precedents. University of Chicago Press.
  16. Chew, E. (2000). Towards a Mathematical Model of Tonality. PhD Dissertation, MIT.
  17. Burgoyne, J. A., Wild, J., & Fujinaga, I. (2011). An expert ground truth set for audio chord recognition and music analysis. Proceedings of ISMIR, 633–638.
  18. White, C. W., & Quinn, I. (2018). Chord context and harmonic function in tonal music. Music Theory Spectrum, 40(2), 314–337.DOI
  19. Caplin, W. E. (1998). Classical Form: A Theory of Formal Functions for the Instrumental Music of Haydn, Mozart, and Beethoven. Oxford University Press.
  20. Temperley, D. (2009). A statistical analysis of tonal harmony. Retrieved from http://davidtemperley.com/kp-stats/
  21. Aldwell, E., Schachter, C., & Cadwallader, A. (2018). Harmony and Voice Leading (5th ed.). Cengage.
  22. Farbood, M. M. (2012). A parametric, temporal model of musical tension. Music Perception, 29(4), 387–428.DOI
  23. Abdallah, S., & Plumbley, M. (2009). Information dynamics: Patterns of expectation and surprise in the perception of music. Connection Science, 21(2–3), 89–117.DOI
  24. Sears, D. R. W., Caplin, W. E., & McAdams, S. (2014). Perceiving the classical cadence. Music Perception, 31(5), 397–417.DOI
  25. Jacoby, N., & McDermott, J. H. (2015). Integer ratio priors on musical rhythm revealed cross-culturally by iterated reproduction. Current Biology, 27(3), 359–370.
  26. Bigand, E., & Poulin-Charronnat, B. (2006). Are we "experienced listeners"? A review of the musical capacities that do not depend on formal musical training. Cognition, 100(1), 100–130.DOI
  27. Tillmann, B. (2012). Music and language perception: Expectations, structural integration, and cognitive sequencing. Topics in Cognitive Science, 4(4), 568–584.DOI
  28. Bigand, E., Parncutt, R., & Lerdahl, F. (1996). Perception of musical tension in short chord sequences: The influence of harmonic function, sensory dissonance, horizontal motion, and musical training. Perception & Psychophysics, 58(1), 125–141.DOI

Rhythm

18 sources

  1. London, J. (2012). Hearing in Time: Psychological Aspects of Musical Meter (2nd ed.). Oxford University Press.
  2. London, J. (2004). Hearing in Time. Oxford University Press.
  3. Toussaint, G. T. (2013). The Geometry of Musical Rhythm: What Makes a "Good" Rhythm Good? CRC Press.
  4. Thul, E., & Toussaint, G. T. (2008). Rhythm complexity measures: A comparison of mathematical models of human perception and performance. Proceedings of ISMIR, 663–668.
  5. Witek, M. A. G., Clarke, E. F., Wallentin, M., Kringelbach, M. L., & Vuust, P. (2014). Syncopation, body-movement and pleasure in groove music. PLoS ONE, 9(4), e94446.DOI
  6. Witek, M. A. G., Popescu, T., Clarke, E. F., Hansen, M., Konvalinka, I., Kringelbach, M. L., & Vuust, P. (2017). Syncopation affects free body-movement in musical groove. Experimental Brain Research, 235(4), 995–1005.DOI
  7. Madison, G., Gouyon, F., Ullén, F., & Hörnström, K. (2011). Modeling the tendency for music to induce movement in humans: First predictions from a generalized model. PLoS ONE, 6(1), e14237.DOI
  8. Sioros, G., Miron, M., Davies, M., Gouyon, F., & Madison, G. (2014). Syncopation creates the sensation of groove in synthesized music examples. Frontiers in Psychology, 5, 1036.DOI
  9. Repp, B. H. (1998). A microcosm of musical expression: Quantitative analysis of pianists' timing in the initial measures of Chopin's Etude in E major. JASA, 104(2), 1085–1100.DOI
  10. Large, E. W., & Palmer, C. (2002). Perceiving temporal regularity in music. Cognitive Science, 26(1), 1–37.DOI
  11. Honing, H. (2012). Without it no music: Beat induction as a fundamental musical trait. Annals of the New York Academy of Sciences, 1252, 85–91.DOI
  12. Keil, C. (1987). Participatory discrepancies and the power of music. Cultural Anthropology, 2(3), 275–283.DOI
  13. Butterfield, M. (2010). Participatory discrepancies and the perception of beats in jazz. Music Perception, 27(3), 157–176.DOI
  14. Stupacher, J., Hove, M. J., Novembre, G., Schütz-Bosbach, S., & Keller, P. E. (2016). Musical groove modulates motor cortex excitability: A TMS investigation. Brain and Cognition, 82(2), 127–136.DOI
  15. Agawu, K. (2006). Structural analysis or cultural analysis? Competing perspectives on the "Standard Pattern" of West African rhythm. Journal of the American Musicological Society, 59(1), 1–46.DOI
  16. Pressing, J. (1983). Cognitive isomorphisms between pitch and rhythm in world musics. Studies in Music, 17, 38–61.
  17. Kilchenmann, L., & Senn, O. (2015). Microtiming in swing and funk affects the body movement behavior of music expert listeners. Frontiers in Psychology, 6, 1232.DOI
  18. Grahn, J. A., & Brett, M. (2007). Rhythm and beat perception in motor areas of the brain. Journal of Cognitive Neuroscience, 19(5), 893–906.DOI

Emotion & Cognition

26 sources

  1. Huron, D. (2006). Sweet Anticipation: Music and the Psychology of Expectation. MIT Press.
  2. Huron, D. (2016). Aesthetics. In S. Hallam, I. Cross, & M. Thaut (Eds.), The Oxford Handbook of Music Psychology (2nd ed., pp. 233–245). Oxford University Press.
  3. Huron, D. (2001). Tone and voice: A derivation of the rules of voice-leading from perceptual principles. Music Perception, 19(1), 1–64.DOI
  4. Meyer, L. B. (1956). Emotion and Meaning in Music. University of Chicago Press.
  5. Juslin, P. N. (2013). From everyday emotions to aesthetic emotions: Towards a unified theory of musical emotions. Physics of Life Reviews, 10(3), 235–266.DOI
  6. Juslin, P. N., & Sloboda, J. A. (2001). Music and Emotion: Theory and Research. Oxford University Press.
  7. Zentner, M., Grandjean, D., & Scherer, K. R. (2008). Emotions evoked by the sound of music: Characterization, classification, and measurement. Emotion, 8(4), 494–521.DOI
  8. Grewe, O., Nagel, F., Kopiez, R., & Altenmüller, E. (2007). Listening to music as a re-creative process: Physiological, psychological, and psychoacoustical correlates of chills and strong emotions. Music Perception, 24(3), 297–314.DOI
  9. Blood, A. J., & Zatorre, R. J. (2001). Intensely pleasurable responses to music correlate with activity in brain regions implicated in reward and emotion. PNAS, 98(20), 11818–11823.DOI
  10. Salimpoor, V. N., Benovoy, M., Larcher, K., Dagher, A., & Zatorre, R. J. (2011). Anatomically distinct dopamine release during anticipation and experience of peak emotion to music. Nature Neuroscience, 14(2), 257–262.DOI
  11. Brattico, E., Bogert, B., & Jacobsen, T. (2013). Toward a neural chronometry for the aesthetic experience of music. Frontiers in Psychology, 4, 206.DOI
  12. Gabrielsson, A., & Lindström, E. (2010). The role of structure in the musical expression of emotions. In P. N. Juslin & J. A. Sloboda (Eds.), Handbook of Music and Emotion (pp. 367–400). Oxford University Press.
  13. Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social Psychology, 39(6), 1161–1178.DOI
  14. Dalla Bella, S., Peretz, I., Rousseau, L., & Gosselin, N. (2001). A developmental study of the affective value of tempo and mode in music. Cognition, 80(3), B1–B10.DOI
  15. Eerola, T. (2011). Are the emotions expressed in music genre-specific? An audio-based evaluation of datasets spanning classical, film, pop and mixed genres. Journal of New Music Research, 40(4), 349–366.DOI
  16. Costa, M., Fine, P., & Bitti, P. E. R. (2000). Interval distributions, mode, and tonal strength of melodies as predictors of perceived emotion. Music Perception, 22(1), 1–14.
  17. Bowling, D. L., Gill, K., Choi, J. D., Prinz, J., & Purves, D. (2010). Major and minor music compared to excited and subdued speech. JASA, 127(1), 491–503.DOI
  18. Gomez, P., & Danuser, B. (2007). Relationships between musical structure and psychophysiological measures of emotion. Emotion, 7(2), 377–387.DOI
  19. Vonnegut, K. (1981). Palm Sunday: An Autobiographical Collage. Delacorte Press.
  20. Lahdelma, I., & Eerola, T. (2016). Single chords convey distinct emotional qualities to both naïve and expert listeners. Psychology of Music, 44(1), 37–54.DOI
  21. Pallesen, K. J., Brattico, E., Bailey, C. J., Korvenoja, A., Koivisto, J., Gjedde, A., & Carlson, S. (2005). Emotion processing of major, minor, and dissonant chords. Annals of the New York Academy of Sciences, 1060, 450–453.
  22. Schubert, E. (2004). Modeling perceived emotion with continuous musical features. Music Perception, 21(4), 561–585.DOI
  23. Simonton, D. K. (1984). Melodic structure and note transition probabilities: A content analysis of 15,618 classical themes. Psychology of Music, 12(1), 3–16.DOI
  24. Simonton, D. K. (1994). Computer content analysis of melodic structure: Classical composers and their compositions. Psychology of Music, 22(1), 31–43.DOI
  25. Pearce, M. T., & Wiggins, G. A. (2006). Expectation in melody: The influence of context and learning. Music Perception, 23(5), 377–405.DOI
  26. Pearce, M. T. (2018). Statistical learning and probabilistic prediction in music cognition: Mechanisms of stylistic enculturation. Annals of the New York Academy of Sciences, 1423(1), 378–395.DOI

Timbre & Production

15 sources

  1. Grey, J. M. (1977). Multidimensional perceptual scaling of musical timbres. JASA, 61(5), 1270–1277.DOI
  2. McAdams, S., Winsberg, S., Donnadieu, S., De Soete, G., & Krimphoff, J. (1995). Perceptual scaling of synthesized musical timbres. JASA, 97(3), 1769–1784.DOI
  3. Zacharakis, A., Pastiadis, K., & Reiss, J. D. (2014). An interlanguage study of musical timbre semantic dimensions and their acoustic correlates. Music Perception, 31(4), 339–358.DOI
  4. Siedenburg, K., Fujinaga, I., & McAdams, S. (2016). A comparison of approaches to timbre descriptors in music information retrieval and music psychology. Journal of New Music Research, 45(1), 27–41.DOI
  5. Eronen, A. (2000). Comparison of features for musical instrument recognition. Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 19–22.
  6. Herrera, P., Amatriain, X., Batlle, E., & Serra, X. (2003). Towards instrument segmentation for music content description: A critical review of instrument classification techniques. Proceedings of ISMIR.
  7. Peeters, G. (2004). A large set of audio features for sound description. CUIDADO Project Technical Report.
  8. Katz, B. (2002). Mastering Audio: The Art and the Science. Focal Press.
  9. Katz, B. (2015). Mastering Audio: The Art and the Science (3rd ed.). Focal Press.
  10. Pestana, P. D., Ma, Z., Reiss, J. D., Barbosa, A., & Black, D. A. A. (2013). Spectral characteristics of popular commercial recordings 1950–2010. AES 135th Convention.
  11. Deruty, E., & Tardieu, D. (2014). About dynamic processing in mainstream music. Journal of the Audio Engineering Society, 62(1/2), 42–55.DOI
  12. Vickers, E. (2010). The loudness war: Background, speculation and recommendations. AES 129th Convention.
  13. Giannoulis, D., Massberg, M., & Reiss, J. D. (2012). Digital dynamic range compressor design — A tutorial and analysis. Journal of the Audio Engineering Society, 60(6), 399–408.
  14. Kramarz, V. (2019). Songwriting in practice: From inspiration to release. Journal of Popular Music Education, 3(2), 189–210.
  15. Covach, J. (2005). Form in rock music: A primer. In D. Stein (Ed.), Engaging Music: Essays in Music Analysis (pp. 65–76). Oxford University Press.

Psychoacoustics

6 sources

  1. Zwicker, E., & Fastl, H. (2007). Psychoacoustics: Facts and Models (3rd ed.). Springer.
  2. Fletcher, H., & Munson, W. A. (1933). Loudness, its definition, measurement and calculation. Bell System Technical Journal, 12(4), 377–430.
  3. Moore, B. C. J. (2012). An Introduction to the Psychology of Hearing (6th ed.). Brill.
  4. ITU-R BS.1770-4 (2015). Algorithms to measure audio programme loudness and true-peak audio level. International Telecommunication Union.
  5. Parncutt, R. (1989). Harmony: A Psychoacoustical Approach. Springer.
  6. Sundberg, J. (1987). The Science of the Singing Voice. Northern Illinois University Press.

Music Psychology

10 sources

  1. Palmer, S. E., Schloss, K. B., Xu, Z., & Prado-León, L. R. (2013). Music–color associations are mediated by emotion. PNAS, 110(22), 8836–8841.DOI
  2. Ward, J., Huckstep, B., & Tsakanikos, E. (2006). Sound-colour synaesthesia: to what extent does it use cross-modal mechanisms common to us all? Cortex, 42(2), 264–280.DOI
  3. Scriabin, A. (1910). Prometheus: The Poem of Fire, Op. 60. Score with clavier à lumières part.
  4. Whiteford, K. L., Schloss, K. B., Helwig, N. E., & Palmer, S. E. (2018). Color, music, and emotion: Bach, Brahms, and Debussy. i-Perception, 9(6).DOI
  5. Temperley, D., & Tan, D. (2013). Emotional connotations of diatonic modes. Music Perception, 30(3), 237–257.DOI
  6. Temperley, D., & Marvin, E. W. (2008). Pitch-class distribution and the identification of key. Music Perception, 25(3), 193–212.DOI
  7. Rechberger, H. (2018). Scales and Modes in Western Music. Fennica Gehrman.
  8. Burns, E. M. (1999). Intervals, scales, and tuning. In D. Deutsch (Ed.), The Psychology of Music (2nd ed., pp. 215–264). Academic Press.
  9. Gill, K. Z., & Purves, D. (2009). A biological rationale for musical scales. PLoS ONE, 4(12), e8144.DOI
  10. Pachet, F., & Cazaly, D. (2000). A taxonomy of musical genres. Proceedings of RIAO, Content-Based Multimedia Information Access.

Audio Science

2 sources

  1. Jiang, D.-N., Lu, L., Zhang, H.-J., Tao, J.-H., & Cai, L.-H. (2002). Music type classification by spectral contrast feature. Proceedings of ICME, 113–116.
  2. Temperley, D. (2007). Music and Probability. MIT Press.

Spatial Audio

3 sources

  1. Barron, M. (1993). Auditorium Acoustics and Architectural Design. E & FN Spon.
  2. Beranek, L. (2004). Concert Halls and Opera Houses: Music, Acoustics, and Architecture (2nd ed.). Springer.
  3. Jot, J.-M., & Chaigne, A. (1991). Digital delay networks for designing artificial reverberators. AES 90th Convention.

How to Cite

Zeltor Labs. (2026). MusicMind Research Bibliography. Retrieved from https://zeltorlabs.com/research/bibliography

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