BIBLIOGRAFIA

Obres de referència.

Cognició musical.

• Balaban, M. (1989). Music Structures: A Temporal-Hierarchical Representation for Music. Musikometrika, 2.
• Bregman, A. S. (1990). Auditory scene analysis: the Perceptual Organisation of Sound. Cambridge, MA: MIT Press.
• Butler, D. (1992). The musician's guide to perception and cognition. New York: Schirmer.
• Clarke, E.F. (1987). Levels of structure in the organisation of musical time. In "Music and psychology: a mutual regard", edited by S. McAdams. Contemporary Music Review, 2(1).
• Clarke, E.F. (1988). Generative principles in music performance. In J. A. Sloboda (ed.),Generative processes in music: The psychology of performance, improvisation and composition. Oxford: Science Publications.
• Clarke, E.F. (1993). Generativity, Mimesis and the Human Body in Music Performance. In I. Cross and I. Deliège (eds.), Music and the Cognitive Sciences. London: Harwood Press, 207-220.
• Deutsch, D. (1982). The psychology of music. Orlando, FL, Academic Press.
• Dowling, W. J., & Harwood, D. L. (1986). Music cognition. San Diego, CA, Academic Press.
• Gabrielsson, A. (1987). Action and perception in rhythm and music. Papers given at a symposium in the Third International Conference on Event Perception and Action. Stockholm, Royal Swedish Academy of Music.
• Jones, M.R., & S. Holleran (1992). Cognitive bases of musical communication. Washington, DC, American Psychological Association.
• Handel, S. (1989). Listening. Cambridge, MA, MIT Press.
• Lehrdahl, F. & Jackendoff, R. (1983). A generative theory of tonal music. MIT, Cambridge, MA.
• Longuet-Higgins, H.C. (1994). Artificial Intelligence and Musical Cognition, Philosophical Transactions of The Royal Society of London -Physical Sciences and Engineering, 349(1689), 103-113.
• McAdams, S. & Bigand, E. (1993). Thinking in sound: the cognitive psychology of human audition. Oxford: Oxford University Press.
• McAdams, S. & Deliège, I. (1989). Music and the Cognitive Sciences. London, Harwood.
• Meyer, L. (1956). Emotion and meaning in music. Chicago, University of Chicago Press.
• Narmour, E. (1990). The Analysis and Cognition of Basic Melodic Structures. Chicago, University of Chicago Press.
• Narmour, E. (1992). The Analysis and Cognition of Melodic Complexity: The Implication-Realization model. Chicago, University of Chicago Press.
• Roederer, J.G. (1975). Introduction to the Physics and Psychoacoustics of Music, 2nd ed. Heidelberg: Springer-Verlag, 1975.
• Seashore, C.E. (1938). Psycholgy of music. New York, McGraw-Hill. (Reissued 1967 by Dover, New York).
• Sloboda, J.A. (1985). The Musical Mind: The Cognitive Psychology of Music. Oxford, Oxford University Press.
• Sloboda, J.A. (1988). Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition. Oxford, Oxford University Press.
• Sundberg, J. (1983). Studies of music performance. Stockholm, Royal Swedish Academy of Music, No. 39.
• West, R., P. Howell, & I. Cross (1985). Musical Structure and Cognition. London: Academic Press.



Anàlisi i síntesi del so, Informàtica musical.

• Balaban, M., Ebcioglu, K . & O. Laske (eds.) (1992). Understanding Music with AI: Perspectives on Music Cognition. Cambridge, Mass.: MIT Press.
• Cope, D. (1991). Computers and Musical Style. Madison, Wis. : A-R Editions, c1991.
• Dodge, Ch. & T.A. Jerse (1985). Computer music : synthesis, composition, and performance. New York, Schirmer Books.
• Laske, O. (1995). Understanding Music with AI. Cambridge, MA: MIT.
• Loy, G. (1988). Composing with Computers - A Survey of Some Compositional Formalisms and Music Programming Languages. In M. V. Matthews & J. R. Pierce (eds.), Current Directions in Computer Music Research. Cambridge, MA: MIT Press.
• Moore, F. R. (1990). Elements of Computer Music. Englewood Cliffs, New Jersey: Prentice- Hall.
• Oppenheim, A. & Nawab, S.H. (1992). Symbolic and Knowledge-Based Signal Processing. Prentice-Hall, 1992.
• Pressing, J. (1992), Synthesizer performance and real-time techniques. Madison, Wis, A-R Editions.
• Roads, C. & J. Strawn (1985). Foundations of Computer Music. Cambridge, MA: MIT Press.
• Roads, C. (1989). The Music Machine Cambridge, MA: MIT Press.
• Roads, C. (1996). The Computer Music Tutorial Cambridge, MA: MIT Press.
• Rowe, R. (1993). Interactive Music Systems: Machine Listening and Composing. MIT press: Cambridge.



Expressió musical.

• Davies, S. (1994). Musical Meaning and Expression. Cornell University Press.
• Kivy, P. (1980). The Corded Shell: Reflections on Musical Expression. Princeton University Press.
• Neumann, F. (1986). Ornamentation and improvisation in Mozart. New Jersey: Princeton University Press.





Tècniques específiques d'Anàlisi i Síntesi

• Anderson, D.P. & R. Kuivila (1990). A System for Computer Music Performance. ACM Transactions on Computer Systems, 8(1), 56-82.
• Anderson, D.P. & R. Kuivila (1991). Formula: A Programming Language for Expressive Computer Music. IEEE Computer, 24(7), 12-21.
• Beauchamp, J. W. (1969). A computer system for time-variant harmonic analysis and synthesis of musical tones, in H. von Foerster & J.W. Beauchamp (eds), Music by Computers, New York: Wiley.
• Fitz, K. (1992). A sinusoidal model for time- and frequency-scale modification in computer music, M.S. Thesis, University of Illinois at Urbana-Champaign, Urbana, IL, 1992.
• Fitz,K. (1993). Lemur Manual. CERL Sound Group, University of Illinois, 1993.
• Hawley, M. (1993) Structure of Sound. Ph.D. Thesis, MIT Media Laboratory.
• Kashino, K., Nakadai, K., Kinoshita, T, Tanaka, H. (1995). Organization of hierarchical perceptual sounds: Music scene analysis with autonomous processing modules and a quantitative information integration mechanism, Proceedings of the International Joint Conference on Artificial Intelligence, Montr‚al.
• Lee, M., and D. Wessel. (1992). Connectionist Models for Real-Time Control of Synthesis and Compositional Algorithms. Proceedings of the 1992 International Computer Music Conference. San Francisco: International Computer Music Association.
• Maher, R. (1990). Evaluation of a method for separating digitized duet signals. Journal of the Audio Engineering Society, 38(12).
• Mellinger, D.K. (1991). Event formation and separation in musical sound. Ph.D. thesis, CCRMA, Stanford University.
• McAulay, R.J., & T.F. Quatieri (1986). Speech Analysis/Sinthesis based on a Sinusoidal Representation. IEEE Transactions on Acoustics, Speech and Signal Processing, 34(4), 744-754.
• Moorer, J. (1975). On the segmentation and Analysis of Continuous Musicla Sound by Digital Computer. Ph.D. thesis, CCRMA, Stanford University.
• Rapoport, E. (1995). FFT Analysis and Emotional Expression in Opera and Lied Singing. Proceedings of the XI Colloquium on Musical Informatics, Bologna.
• Rodet, X., and P. Cointe. (1984). FORMES: Composition and Scheduling of Processes. Computer Music Journal , 8(3), 32-50. Reprinted in S. T. Pope (ed), 1991, The Well-Tempered Object: Musical Applications of Object-Oriented Software Technology. Cambridge, MA: MIT Press.
• Sciarabba, J. T. (1991). Psychoacoustics in sound synthesis, M.S. thesis, University of Illinois at Urbana-Champaign, Urbana, IL, 1991.
• Schloss, W.A. (1985). On the Automatic Transcription of Percussive Music -from Acoustical Signal to High-Level Analysis. Ph.D. thesis, CCRMA-Stanford University.
• Serra, X. (1989). A system for sound analysis/transformation/synthesis based on a deterministic plus stochastic decomposition. Department of Music Report No. STAN-M-58, Ph.D. dissertation, Center for Computer Music Research in Music and Acoustics, Stanford University.
• Serra, X. (in press) Musical Sound Modeling with Sinusoids plus Noise. In G. De Poli, A. Picialli, S. , T. Pope, & C. Roads (eds.), Musical Signal Processing. Cambridge, Mass.: MIT Press.
• Stautner, J. (1982). The Auditory Transform. Master's thesis, MIT.





Treballs amb implementacions informàtiques d'aspectes d'expressió musical.

• Albright, L.E. (1988). Computer realization of human music cognition. Ph.D. thesis. North Texas State University.
• Allen, P. & R. Dannenberg (1990). Tracking musical beats in real time. Proceedings of the 1990 ICMC, 140-143.
• Ariyoshi, Y., Shimojo, S., & Miyahara, H. (1995). Hyperscore: A Design of a Hypertext Model for Musical Expression and Structure. Journal of New Music Research, 24, 130-147.
• Battel, G.U. & R. Bresin (1993). Analysis by Synthesis in Piano Performance: a Study on the Theme of the Brahms "Variations on a Theme of Paganini op. 35.", Proc. of the 1993 SMAC (Stockholm Music Acoustic Conference), Stockholm.
• Battel G.U., R. Bresin, G. De Poli, A. Vidolin (1993). Automatic performance of musical scores by mean of neural networks: evaluation with listening tests, Proc. of X Colloquio di Informatica Musicale, 97-101, Milano.
• Battel G.U., Bresin R., G. De Poli, A. Vidolin (1994). Neural networks vs. rules system: evaluation tests of automatic performance of musical scores, Proc. of the 1994 ICMC (International Computer Music Conference), Aarhus.
• Beauchamp, J. W. (1981). Data reduction and resynthesis of connected solo passages using frequency, amplitude, and `brightness' detection and the nonlinear synthesis technique, in Proceedings of the 1981 International Computer Music Conference, Denton, Texas: North Texas State University, 316-323.
• Bilmes, J. (1993). Timing is of essence: Perceptual and computational techniques for representing, learning, and reproducing expressive timing in percusive rhythm. Master's thesis, MIT Media Laboratory.
• Bresin R. (1993). MELODIA: a program for performance rules testing, teaching, and piano scores performing, Proceedings of the X Colloquio di Informatica Musicale, Milano, pp. 325-327.
• Bresin R., G. De Poli, A. Vidolin, (1991). A connectionist approach to timing deviation control in musical performance, Proc. of Secondo Convegno Europeo di Analisi Musicale, pp. 635-638, Universita' degli Studi di Trento.
• Bresin, R., G. De Poli, A. Vidolin (1991). Un approccio connessionistico per il controllo dei parametri nell'esecuzione musicale, Proceedings of the IX Colloquio di Informatica Musicale, Genova, 88-102.
• Bresin, R., G. De Poli, A. Vidolin (1992). Symbolic and sub-symbolic rules system for real time score performance, Proceedings of the 1992 ICMC, International Computer Music Association, San Francisco, pp. 211-214.
• Bresin R., De Poli G., Vidolin A. (1993). A Neural Networks Based System for Automatic Performance of Musical Scores, Proc. of the 1993 SMAC (Stockholm Music Acoustic Conference), Stockholm.
• Bresin, R., C. Vecchio (1994). Analysis and synthesis of the performing action of a real pianist by means of artificial neural networks, Proceedings of the 3rd ICMPC (International Conference for Music Perception and Cognition), University of Liege.
• Chafe, C. (1989). Simulating performance on a bowed instrument. In M. Mathews & J. Pierce (eds.) Current Directions in Computer Music Research. Cambridge, MIT Press. 185-198.
• Dannenberg, R.B. & B. Mont-Reynaud (1987). Following an improvisation in real-time. In Proceedings of the 1987 International Computer Music Conference. 241 - 248. San Francisco: International Computer Music Association.
• Dannenberg, R.B. (1993). Music Understanding by Computer. In Proceedings of the IAKTA Workshop on Knowledge Technology in the Arts. 41-55. Osaka: IAKTA/LIST.
• De Poli G., L. Irone, A. Vidolin, (1990), Music score interpretation using a multilevel knowledge base, Interface, vol. 19, pp. 137-146.
• Desain, P. (1992a). A (de)composable theory of rhythm perception. Music Perception, 9(4), 439-454.
• Desain, P. (1992b). Can computer music benefit from cognitive models of rhythm perception? In Proceedings of the 1992 International Computer Music Conference. 42-45. San Francisco: International Computer Music Association.
• Desain, P. (1993). A connectionist and a traditional AI quantizer, symbolic versus sub-symbolic models of rhythm perception. Contemporary Music Review, 9, 239-254.
• Desain, P., & Honing, H. (1988). LOCO: a composition microworld in Logo. Computer Music Journal , 12(3), 30-42.
• Desain, P., & Honing, H. (1989). Quantization of musical time: a connectionist approach. Computer Music Journal , 13:56-66.
• Desain, P., & Honing, H. (1991). Quantization of musical time: a connectionist approach. In P.M. Todd and D. G. Loy (eds.), Music and Connectionism. Cambridge: MIT Press.
• Desain, P., & Honing, H. (1991). Towards a calculus for expressive timing in music. Computers in Music Research, 3, 43-120.
• Desain, P. & Honing, H. (1991). Tempo curves considered harmful. A critical review of the representation of timing in computer music. In Proceedings of the 1991 International Computer Music Conference (Montreal). San Francisco: Computer Music Association, 1990. Also in P. Desain & H. Honing (1992). Music, mind, and machine.
• Desain, P. & Honing, H. (1992). Music, Mind, and Machine: Studies in computer music, music cognition and artificial intelligence. Amsterdam, Thesis Publishers.
• Desain, P. & Honing, H. (1992). Towards a calculus for expressive timing in music. Computers in Music Research, Vol. 3. Also in P. Desain & H. Honing (1992). Music, mind, and machine.
• Desain, P., & Honing, H. (1992). Musical machines: can there be? are we? Some observations on- and a possible approach to- the computational modelling of music cognition. In C. Auxiette, C. Drake, & C. Gerard (eds.), Proceedings of the Fourth International Workshop on Rhythm Perception and Production. 129-140. Bourges.
• Desain, P., & Honing, H. (1992). Time functions function best as functions of multiple times. Computer Music Journal, 16(2), 17-34.
• Desain, P., & Honing, H. (1993). CLOSe to the edge? Multiple and mixin inheritance, multi methods, and method combination as techniques in the representation of musical knowledge. In Proceedings of the IAKTA Workshop on Knowledge Technology in the Arts. 99-106. Osaka: IAKTA/LIST.
• Desain, P., & Honing, H. (1993). On Continuous Musical Control of Discrete Musical Objects. In Proceedings of the 1993 International Computer Music Conference. San Francisco: International Computer Music Association.
• Desain, P., & Honing, H. (1994). Advanced issues in beat induction modeling: syncopation, tempo and timing. In Proceedings of the 1994 International Computer Music Conference. 92-94. San Francisco: International Computer Music Association.
• Desain, P., & Honing, H. (1994). Does expressive timing in music performance scale proportionally with tempo? Psychological Research, 56, 285-292.
• Desain, P., & Honing, H. (1994). Rule-based models of initial beat induction and an analysis of their behavior. In Proceedings of the 1994 International Computer Music Conference. 80-82. San Francisco: International Computer Music Association.
• Desain, P., & Honing, H. (1994). Can music cognition benefit from computer music research? From foot-tapper systems to beat induction models. In Proceedings of the ICMPC 1994. 397-398. Liege: ESCOM.
• Desain, P., & Honing, H. (1995). Computational models of beat induction: the rule-based approach. Proceedings of IJCAI 1995. Montreal: IJCAI.
• Desain, P., and H. Honing (1995). Towards algorithmic descriptions of continuous modulations in musical parameters. In Proceedings of the 1995 International Computer Music Conference. San Francisco: International Computer Music Association.
• Desain, P. & S. de Vos. (1990). Autocorrelation and the study of musical expression. In Proceedings of the 1990 International Computer Music Conference (Glasgow). San Francisco: Computer Music Association, 1990. Also in P. Desain & H. Honing (1992). Music, mind, and machine.
• Friberg, A (1991). Generative Rules for Music Performance: A Formal Description of a Rule System, Computer Music Journal , 15 (2), 56-71.
• Friberg, A., Fryd‚n, L, Bodin, L, & Sundberg, J. (1991). Performance rules for computer-controlled contemporary keyboard music. Computer Music Journal, 15(2), 49-55.
• Garton, B. (1992). Virtual Performance Modelling. Proceedings of the 1992 International Computer Music Conference. San Francisco: ICMA.
• Helmuth, M.M. (1994). "Meeting the dreamer": An exploration of computer music composition. D.M.A. thesis. Columbia University.
• Honing, H. (1990). POCO: an environment for analysing, modifying, and generating expression in music. In Proceedings of the 1990 International Computer Music Conference (Glasgow). San Francisco: Computer Music Association, 1990. Also in P. Desain & H. Honing (1992). Music, mind, and machine.
• Honing, H. (1992). Expresso, a strong and small editor for expression. In Proceedings of the 1992 International Computer Music Conference. 215-218. San Francisco: International Computer Music Association.
• Honing, H. (1993a). A microworld approach to the formalization of musical knowledge. Computers and the Humanities, 27, 41-47.
• Honing, H. (1993b). Issues in the representation of time and structure in music. Contemporary Music Review, 9, 221-239.
• Honing, H. (1995). The vibrato problem, comparing two solutions. Computer Music Journal , 19(3)
• Johnson, M.L. (1991). Toward an expert system for expressive musical performance. IEEE Computer, 24(7), 30-34.
• Katayose, H. & Inokuchi, S. (1989). The kansei music system. Computer Music Journal , 12(4), 1989.
• Katayose, H., Fukuoka, T., Takami, K, & Inokucho, S. (1990). Expression extraction in virtuoso music performances. In Proceedings of the Tenth International Conference on Pattern Recognition. Atlantic City, NJ, 780-784.
• Noike, K., N. Takiguchi, T. Nose, Y. Kotani, & H. Nisimura (1993). Automatic Generation of Expressive Performance by Using Music Structures. In Proceedings of the International Computer Music Conference (ICMC-93), Tokyo, Japan. San Francisco, CA: International Computer Music Association.
• Oosten , P. van (1993). A Critical Sudy of Sundbergs' Rules for Expression in the Performance of Melodies. Contemporary Music Review, 9, 267-274.
• Pelz-Sherman, M. (199?) On the Formalization of Expression in Music Performed by Computers. M.Sc. thesis, University of California San Diego.
• Pope, S. T. (1986). The Development of an Intelligent Composer's Assistant: Interactive Graphics Tools and Knowledge Representation for Composers. Proceedings of the 1986 International Computer Music Conference. San Francisco: International Computer Music Association. pp. 131-144.
• Pope, S. T. (1991). A Tool for Manipulating Expressive and Structural Hierarchies in Music (or, `TR-Trees in the MODE: A Tree Editor based Loosely on Fred's Theory'). Proceedings of the International Computer Music Conference. San Francisco: International Computer Music Association.
• Pennycook, B., D.R. Stammen, & D. Reynolds (1993). Toward a computer model of a jazz improviser. In Proceedings of the 1993 International Computer Music Conference. 228-231. San Francisco: International Computer Music Association.
• Puckette, M. (1990). Amplifying Musical Nuance. Journal of the Acoustical Society of America. 87-S1.
• Rosenthal, D. (1992). Machine Rhythm: Computer Emulation of Human Rhythm Perception. Ph.D. Thesis, Massachusetts Institute of Technology
• Schreirer, E.D. (1993). Extracting Expressive Performance Information from Recorded Music. Master's thesis, MIT.
• Smith, M.W.A. (1995). Virtuoso Pianism from the QWERTY Keyboard: The Electronic Realization of Liszt's Scores. Computers and the Humanities, 29, 285-296.
• Strawn, J. (1985). Modeling musical transitions, Ph.D. dissertation, Stanford University, Stanford, CA.
• Strawn, J. (1987). Analysis and synthesis of musical transitions using the discrete short-time fourier transform, Journal of the Audio Engineering Society, 35(1/2), 3-13, 1987.
• Sundberg, J. (1988). Computer synthesis of music performance. In J.A. Sloboda (ed.) Generative Processes in Music: The Psychology of Performance, Improvisation, and Composition. Oxford, Oxford University Press.
• Sundberg & Verillo (1995). Comments on Feldman, Epstein & Richards (1992) Music Perception. 12(2), 265-266.
• Sundberg, J. & Verillo, V. (1980). On the anatomy of the ritard: A study of timing in music. Journal of the Acoustical Society of America. 68, 772-779.
• Sundberg, J., Askenfelt, A., & Fryden, L. (1983). Musical performance: A synthesis-by-rule approach, Computer Music Journal , 7(1), 37-43.
• Sundberg, J., A. Friberg & L. Fryden (1989). Rules for Automated Performance of Ensemble Music. Contemporary Music Review, 3.
• Sundberg, J, L. Fryden, A. Askenfelt. (1983). What tells you the player is musical? An analysis-by-synthesis study of musical performance, in (J. Sundberg, ed.) Studies of Music Performance Royal Swedish Academy of Music, Stockholm.
• Todd, N.P. (1985). A model of expressive timing in tonal music. Music Perception, 3, 33-58.
• Todd, N.P. (1989). Towards a Cognitive Theory of Expression: The Performance and Perception of Rubato. In S. McAdams & I. DeliŠge (eds.), Music and the Cognitive Sciences. London, Harwood.
• Todd, N.P. (1989). A Computational Model of Rubato. In "Music, Mind and Structure", edited by E. Clarke and S. Emmerson. Contemporary Music Review, 3(1).
• Todd, N.P. (1992). The Dynamics of Dynamics: A Model of Musical Expression. Journal of the Acoustical Society of America, 91(6), 3540-3550.
• Todd, N.P. (1993). Vestibular Feedback in Musical Performance: Response to Somatosensory Feedback in Musical Performance (edited by Sundberg and Verillo). Music Perception. 10(3), 379-382.
• Todd, N.P. (1995). The Kinematics of Musical Expression, Journal of The Acoustical Society of America, 97(3), 1940-1949.
• Truax, B. (1991). Capturing Musical Knowledge in Software Systems. Interface 20(3-4), 217-234.
• Vercoe, B. (1984). The synthetic performer in the context of live performance. In Prceedings of the International Computer Music Conference.
• Widmer, G. (1990). The Usefulness of Qualitative Theories of Musical Perception. In Proceedings of the International Computer Music Conference (ICMC-90), Glasgow, Scotland. San Francisco, CA: International Computer Music Association.
• Widmer, G. (1990). Learning a Complex Musical Task on the Basis of a Plausible Theory of Musical Perception. In Proceedings of the ECAI Workshop on Artificial Intelligence and Music, ECAI-90, Stockholm, Sweden.
• Widmer, G. (1992). Qualitative Perception Modelling and Intelligent Musical Learning. Computer Music Journal 16(2), pp. 51-68, MIT Press.
• Widmer, G. (1992). A Knowledge Intensive Approach to Machine Learning in Music. In M. Balaban, K. Ebcioglu, O. Laske (eds.), Understanding Music with AI: Perspectives on Music Cognition. AAAI Press, Menlo Park, CA.
• Widmer, G. (1992). The Importance of Musicologically Meaningful Vocabularies for Learning. In Proceedings of the International Computer Music Conference (ICMC-92), San Jose. San Francisco, CA: International Computer Music Association.
• Widmer, G. (1993). Understanding and Learning Musical Expression. In Proceedings of the International Computer Music Conference (ICMC-93), Tokyo, Japan. San Francisco, CA: International Computer Music Association.
• Widmer, G. (1994). The Synergy of Music Theory and AI: Learning Multi-Level Expressive Interpretation. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), AAAI Press/MIT Press, Cambridge, MA, pp.114-119.
• Widmer, G. (1994). Learning Expression at Multiple Structural Levels. In Proceedings of the International Computer Music Conference (ICMC-94), Aarhus, Denmark. San Francisco, CA: International Computer Music Association.
• Widmer, G. (1994). Studying Musical Expression with AI and Machine Learning: "Analysis by Resynthesis". In J. Sundberg (ed.), Proceedings of the Aarhus Symposium on Generative Grammars for Music Performance. Royal Institute of Technology (KTH), Stockholm, Sweden.
• Widmer, G. (1995). Modelling the Rational Basis of Musical Expression. Computer Music Journal 19(2), pp.76-96, MIT Press.
• Widmer, G. (1995). A Machine Learning Analysis of Expressive Timing in Pianists' Performances of Schumann's "Träumerei". In A. Friberg and J. Sundberg (ed.), Proceedings of the KTH Symposium on Generative Grammars for Music Performance, Royal Institute of Technology (KTH), Stockholm, Sweden.
• Widmer, G. (1996). Learning Expressive Performance: The Structure-Level Approach. Journal of New Music Research 25(2), pp. 179-205.



Treballs empírics sobre aspectes específics de l'expressió musical

• Brown, J.C. (1993). Determination of meter of musical scores by autocorrelation. J. Acoust. Soc. Am., 94(4), 1953-1957.
• Bigand, E. (1990). Perception et compr‚hension des phrases musicales. Ph.D. thesis, Universit‚ de Nanterre (Paris X), Nanterre [Universal microfiche ISSN: 0294-1767 No. 42, 09882/90, Lille, France.
• Clynes, M. (1983). Expressive Microstructure in Music, liked to Living Qualities. In J.Sundberg (ed.) Studies of Music Performance. Stockholm: Royal Swedish Academy of Music, No. 39.
• Clynes, M. (1987). What can a musician learn about music performance from newly discovered microstructure principles (PM and PAS)? In A. Gabrielson (ed.) Action and Perception in Rhythm and Music, Royal Swedish Academy of Music, No. 55.
• Davidson, J. (1991). The Perception of Expressive Movement in Music Performance. Ph.D. thesis, City University, London.
• Drake, C. and C. Palmer (1991). Recovering structure from expresssion in music performance. Proceedings of Cognitive Science, Chicago.
• Drake, C. and C. Palmer (1993) Accent Structures in Music Performance. Music Perception. 10 (3) 343-378
• Feldman, J. , Epstein, D. & Richards, W. (1992). Force Dynamics of Tempo Change in Music. Music Perception, 10(2), 185-204.
• Kendall, R.A. (1986). The role of acoustic signal partitions in listener categorization of musical phrases. Music Perception, 4, 185-214.
• Kendall, R.A. & Carterette, E.C. (1990). The communication of musical expression. Music Perception, 8, 129-162.
• Lee, C. S. (1985). The rhythmic interpretation of simple musical sequences: towards a perceptual model. In R. West, P. Howell, & I. Cross (eds.) Musical Structure and Cognition. 53-69. London: Academic Press.
• Lee, C.S. (1991). The perception of metrical structure: Experimental evidence and a model. In P. Howell, R. West, & I. Cross (Eds.), Representing musical structure (pp. 59-127). London: Academic Press.
• Longuet-Higgins, H.C. (1995). The structural determinants of musical expression. In M.A. Boden & A. Bundy (Eds.), Artificial Intelligence and the Mind: New Breakthroughs or Dead-Ends? London: The Royal Society and The British Academy.
• Maher, R. & J. Beauchamp (1990). An investigation of vocal vibrato for synthesis,Applied Acoustics, 30, 219-245.
• McArthur, V.H. (1989). The use of computers to analyze performance motions of musicians. Psychomusicology, 8(2), 135-141.
• Palmer, C. (1989). Timing in Skilled Music Performance. Ph.D. Thesis, Cornell University.
• Palmer, C. (1989). Computer graphics in music performance research. Behavior Research Methods, Instruments, and Computers, 21(2), 265-270.
• Palmer, C. (1989). Mapping Musical thought to musical performance. Journal of Experimental Psychology, 15(12).
• Palmer, C. (1989). Structural representations of music performance. Proceedings of the Eleventh Annual Conference of the Cognitive Science Society. Hillsdale, NJ, Erlbaum.
• Palmer, C. (1995). Reduced Memory Representations for Music. Cognitive Science, 19(1), 53-96.
• Palmer, C. & C.L. Krumhansl (1990). Mental representations of musical meter. Journal of Experimental Psychology: Human Perception and performance, 16(4), 728-741.
• Parncutt, R. (1994). A perceptual model of pulse salience and metrical accent in musical rhythms. Music Perception, 11, 409-464.
• Povel, D. J. (1977). Temporal structure of performed music: Some preliminary observations. Acta Psychologica, 41, 309-320.
• Povel D.J. (1981). Internal Representation of Simple Temporal Patterns. Journal of Experimental Psychology: Human Perception and Production, 7(1).
• Rasch, R.A. (1979). Sychronization in Performed Ensemble Music. Acustica 43(2).
• Repp, B. (1990). Patterns of expressive timing in performances of Beethoven minuet by nineteen famous pianists. Journal of the Acoustical Society of America, 88, 622-641.
• Repp, B. H. (1994). Relational Invariance of Expressive Microstructure Across Global Tempo Changes in Music Performance: An Exploratory Study. Psychological Research, 56, 269-284.
• Repp, B.H., (1995). Acoustics, Perception, and Production of Legato Articulation on a Digital Piano. Journal of the Acoustical Society of America, 97(6), 3862-3874.
• Rodriguez, C.X., (1995). Children's perception, production, and description of musical expression. Ph.D. thesis. Northwestern University.
• Shaffer, L.H. (1981). Performances of Chopin, Bach and Bartok; studies in motor programming, Cognitive Psychology, 13, pp. 326-376.
• Sloboda, J. (1991). Musical expertise. In K.A. Ericsson & J. Smith (eds.), Toward a general theory of expertise: Prospects and limits. New York, Cambridge University Press.
• Thompson, W.F., Sundberg, J., Friberg, A., Fryden, L. (1989). The use of rules for expression in the performance of melodies. Psychology of Music, 17(1), 63-82.
• Vos. P. & Handel, S., (1987). Playing Triplets: Facts and Preferences. In: Action and Perception in Rhythm and Music, Edited by A. Gabrielsson. Royal Swedish Academy of Music. No. 55.





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Index

1. Index.
2. Acotament del tema.
3. Recursos Expressius.
4. Bibliografia.
5. Pàgines electròniques relacionades.