Charlotte Truchet is an assistant professor at Nantes University in France. While she was earning her PhD, she worked on musical constraints in collaboration with contemporary composers at IRCAM/University of Paris 6. Gérard Assayag is head of the IRCAM-CNRS lab "Sciences and Technologies for Music and Sound" and a co-author of Open Music Computer-Assisted Composition software.

• Introduction xiiiCharlotte TRUCHET and Gerard ASSAYAGChapter 1. Modeling Temporal Constraints for a System of Interactive Scores 1Antoine ALLOMBERT, Myriam DESAINTE-CATHERINE and Mauricio TORO1.1. Introduction 11.2. Formalism of interactive scores 21.2.1. Temporal relations 31.2.2. Interaction points 41.2.3. Modification behaviors 41.2.3.1. Fermata behavior 51.2.3.2. Chronological and anti-chronological behaviors 51.2.3.3. Proportional behavior 71.3. ECO machine 81.3.1. Supple intervals with fermata behavior 81.3.2. General case 101.3.3. Interval constraints 111.3.4. Constraint propagation 131.4. Concurrent constraint time model 151.4.1. Ntcc model 151.4.1.1. Control points 161.4.1.2. Temporal relations 161.4.1.3. Example 161.4.2. Discussion 171.5. Timed conditional branching model 181.5.1. Specification of the model 181.5.1.1. Control points 191.5.1.2. Intervals 191.5.1.3. Example 201.5.2. Ntcc model 201.5.2.1. Control points 211.5.2.2. Intervals 211.5.2.3. Example 221.5.3. Results and discussion 221.6. Concluding remarks and future work 221.7. Bibliography 23Chapter 2. Variable Orderings for Solving Musical Constraint Satisfaction Problems 25Torsten ANDERS2.1. Motivation 252.2. Background: the constraint model based on computation spaces 282.2.1. Propagate-and-search 292.2.2. An example 332.2.3. Distribution strategy definition 352.3. Specializing the constraint model for music 372.3.1. Music representation and score contexts 372.3.2. Adapting the space-based constraint model 382.4. Score distribution strategies 392.4.1. Adapting the first-fail principle 402.4.2. Resolving inaccessible score contexts 412.4.3. Resolving multiple inaccessible score contexts in order 422.4.4. Combining the principles resolve-inaccessible-contexts and first-fail 442.4.5. The dynamic left-to-right variable ordering 442.5. An example: Florid counterpoint 462.5.1. The music theory model 472.5.2. Search process and results 492.6. Summary 512.7. Bibliography 52Chapter 3. Constraints for an Unfolding Time 55Georges BLOCH and Charlotte TRUCHET3.1. Introduction 563.1.1. Composition? 563.1.2. Writing: the constraints of composition 573.1.3. Composition as a synthesis of time 593.2. A new set of musical problems: the tiling canons 603.2.1. The canon structure 603.2.2. Computer representation 633.2.3. Harmony? 643.2.4. What about time evolution? 663.3. Musical constraints on tiling canons 683.3.1. Harmonic constraints: virtual fundamental 693.3.2. Harmonic constraints: textures 713.3.3. Melodic constraint 723.3.4. Overconstrained and other constraints 733.4. Constraints in time 743.4.1. The solving algorithm 743.4.2. Constraint process as a musical process 763.4.3. Modifying constraints in time 773.5. Conclusion 793.6. Bibliography 79Chapter 4. Global Constraints in Orchestration 81Gregoire CARPENTIER4.1. Introduction 814.2. The automatic orchestration problem 834.3. A unified syntax for global constraints 844.3.1. Preliminary definitions 844.3.2. Constraint operators 844.3.3. Cost functions 854.4. The CDCSolver heuristic 874.4.1. Conflict constraints versus design constraints 874.4.2. Avoiding cycles 894.4.3. Choosing the variable to update 904.4.4. Using CDCSolver in constrained optimization problems 924.5. Performance evaluation 934.6. Using CDCSolver in automatic orchestration 944.6.1. Timbre "fade in" 954.6.2. Speakings ostinato 964.7. Conclusions and future work 1014.8. Bibliography 101Chapter 5. Using Gecode to Solve Musical Constraint Problems 103Serge LEMOUTON5.1. Plan 1045.2. Introduction 1045.3. Why Gecode? 1065.3.1. Constraints in OpenMusic and PWGL 1065.3.2. Gecode 1075.3.3. Gelisp 1075.3.4. OMGecode implementation 1085.4. A musical constraint repertoire 1085.4.1. All-interval 1085.4.1.1. Definitions 1085.4.1.2. Results 1095.4.1.3. Musical uses 1105.4.2. Constrained melodic strings for Michael Jarrell's Congruences 1115.4.2.1. Definition 1115.4.2.2. "Historic" implementations 1135.4.2.3. Gecode implementation and results 1165.4.3. Generating chords by constraints: harmonic rules 1175.4.3.1. Definition 1175.4.3.2. Hamming 1185.4.4. Stroppa vertical pitch structure constraints 1195.4.4.1. Definition 1195.4.5. Harmonic profiles 1215.4.5.1. Definition 1215.4.6. Melodic interpolations 1225.4.7. Harmonic progression 1235.4.7.1. Definition 1235.5. Musical constraint specificities 1235.5.1. Time-varying constraints 1245.5.2. Soft constraints 1245.5.3. Availability and installation 1255.6. Conclusion 1255.7. Bibliography 1255.8. Appendix A: All-interval script command options 1275.9. Appendix B: Jarrell problem implemented in C++, using Gecode 1295.10. Appendix C: Jarrell script command options 130Chapter 6. Concurrent ConstraintModels of Music Interaction 133Carlos OLARTE, Camilo RUEDA, Gerardo SARRIA, Mauricio TORO and Frank D. VALENCIA6.1. Introduction 1336.2. Concurrent constraint programming 1346.2.1. The language of CCP processes 1356.2.2. Timed CCP 1366.3. Dynamic interactive scores 1376.3.1. Mobile behavior in tcc and a model of dynamic interactive scores 1386.4. Non-determinism and verification of musical properties 1406.4.1. The ntcc calculus 1416.4.2. Logic characterization of ntccprocesses 1426.4.3. Modeling rhythm patterns 1436.5. Real time and preemption 1466.6. Probabilistic extensions and musical improvisation 1496.6.1. The factor oracle 1496.6.2. Probabilistic transversal of the FO 1516.7. Perspectives and future work 1526.8. Bibliography 153Chapter 7. From Rhythm Rules to Music Rules 157Orjan SANDRED7.1. Two constraint-solving systems for musical composition 1577.2. Music representation 1587.3. Rhythm representation and OMRC 1597.4. OMRC and rhythm organization 1597.5. Basic concepts for rules in OMRC 1607.6. From OMRC to PWMC 1617.7. Basic concepts in PWMC 1637.8. The user interface 1657.9. More about the domains 1667.9.1. Motif and groupings of values 1677.9.2. Metric units 1687.9.3. Locked variables 1687.10. Defining rules 1697.10.1. Access boxes 1707.10.2. Logic statements 1727.11. Heuristic rules 1737.12. A patch example 1747.13. Strategy rules 1777.14. Data representation 1787.14.1. The domain 1787.14.2. Score representation 1797.15. Musical example: Labyrinths in the Wind 1837.15.1. Rules for rhythm 1837.15.2. Rules for pitch 1857.15.3. A heuristic stochastic rule 1857.15.4. Examining the solution 1867.16. Conclusion and future developments of the systems 1877.17. Bibliography 188Chapter 8. OMClouds, a Library for Musical Constraints 189Charlotte TRUCHET8.1. Introduction 1898.1.1. OpenMusic 1908.1.2. Constraints in CAC 1928.2. Some musical CSPs 1938.2.1. All-intervals series 1938.2.2. Sorting chords 1948.2.3. Asynchronous rhythms 1948.2.4. Spectral chords 1968.2.5. Gestures 1988.2.6. Tempo approximation 1998.2.7. Accelerando 2008.2.8. Other problems 2018.2.9. Conclusions on the compositional CSPs 2028.3. OMClouds 2048.3.1. Adaptive search 2048.3.2. CSP definition 2058.3.3. Generation of the error functions 2078.3.4. Solving 2088.3.5. Edition of results 2098.4. Conclusion 2118.5. Bibliography 211List of Authors 215Index 219