Computer Models of Musical Creativity

Computer Models of Musical Creativity
Chapter 3: Current Models of Musical Creativity

• Although randomness often competes with creativity in terms of surprise, it is no substitute for a creative process
• Most random processes are simply too complex to predict
• Randomness arises from a lack of predictability using logic, not a lack of determinism
• Good creativity simply requires good algorithms
• Some models of creativity include cellular automata, mathematical models, fuzzy logic, neural networks, and Markov chains
• Using Markov chains, one can analyze a piece of music and produce new music in roughly the same style
• Genetic algorithms operate on the principle of natural selection
• Genetic algorithms and cellular automata can both generate very complex output
  
• In rule-based programs, creativity really belongs to the programmer, not the program
• Neural networks use "hidden unit" networks to simulate the output of a given situation based on a sample input and output
• Neural networks simulate the workings of the human brain
• Mathematical formulas can be used to produce quasi randomness
• 
  
• "Randomness is not an engaging mystery, but a simple reflection of ignorance"
  
• "Randomness refers to behavior that is either too complex, too patternless, or too irrelevant to make prediction possible"
• "For those believing that using algorithms to create music somehow removes imagination, inspiration, and intuition from the composing process, know that defining a good algorithm requires as much imagination, inspiration, and intuition as does composing a good melody or harmony"
• "Neither good algorithms nor good musical ideas grow on trees"
• "Integrating association-based procedures with data-driven processes increases the creative potential of this approach to music composition"
• "GAs typically involve DNA-like inheritance of characteristics as well as crossover and mutation techniques to develop new traits"
• "Neural networks then cycle through a series of forward or back propagations that compare output with input and alter hidden unit values, until the output values match or approximate the relationships of the input and output data upon which they were trained"
• "Sandwiched between these nodes are variable numbers of layers of hidden units, as well as variable numbers of connections between these inputs, outputs, and hidden units, making the training process extremely complex"
• "We should not overestimate the abilities of neural networks or let comtivity mask a lack of true creativity"
• "Mathematical origins for algorithmic music, while occasionally producing interesting results, in no way indicate the presence of creativity"
• "Computer programs must be sufficiently independent of their programmers and users in order to qualify as truly creative. Most apparently creative algorithmic composing programs either produce enormous output from which users make preferential choices or invoke so many programmer-defined rules that the software only proves the creativity of the programmer"
  

These constitute the notes I took on my reading today.

Computer Models of Musical Creativity

Computer Models of Musical Creativity
Chapter 2: Background

• Surprise is a necessary ingredient in creativity
• Associationism - a view that creativity stems of unconscious or subconscious associations - linking thoughts, ideas, experiences, and images
• Letter Spirit, a program used to creatively make new fonts, operates with decision waves - unifying operations that consist of "the gradual, slow-but-sure tightening up of internal consistency all across the structure under construction"
• Cope feels that focusing on details is not the important part of a creative work
• The Turing test may also be an adequate gauge of creativity
• Creativity is not an output, rather, it is a function
• Creativity is not necessarily audible - it is only perceptible when the method of creation is known
  
• "Most recent research in artificial intelligence and creativity tends to focus on connectionism, geneticism, and expertism"
  
• "Full-scale creativity consists in having a keen sense for what is interesting, following it recursively, applying it at the meta-level, and modifying it accordingly" - Hofstadter
• "I do not believe ... that all humans share a common aesthetic"
• "It is the processes, rather than their output, that best identify creativity"
• "The results of creativity should be different from the results of other processes"
• "Creativity is a process, not the result of a process"
  

These constitute the notes I took on my reading today.

Computer Models of Musical Creativity

Computer Models of Musical Creativity
Chapter 1: Definitions

• Many see creativity as restricted to humans
• If humans can't create creative machines, then are they really creative in the first place?
• Two important questions when considering creativity: must the creator know what he or she is creating and must they appreciate his or her own creation?
• Creativity is directly related to intelligence
• Intelligence consists of the following abilities: to learn, to remember, to infer, to analogize, and to create
• Combinatorial accidents can be powerful creative tools and also produce striking originality
  
• "Originality must be useful"
• "Cross-wiring can produce interesting, unique, and important creative connections"
• "Vertically thinking is selective and analytical, while lateral thinking is generative and instigative"
• Cope's definition of creativity: "The initialization of connections between two or more multifaceted things, ideas, or phenomena hitherto not otherwise considered actively connected"
• "I do not feel that creativity requires intelligence, nor does it consequently require life"
• "Creativity should never be confused with arbitrary or convenient contrivances that simply take any road untried for the sake of novelty"
  

These constitute the notes I took on my reading today.

Music, the Brain, and Ecstasy

Music, the Brain, and Ecstasy
Chapter 6: Composition

• Imagery describes what perception cannot
  
• The brain always works through abstract hierarchies, connecting ideas with a web of relations rather than storing a single data bank for a specific subject
  
• Composers' brains group notes, chords, and progressions with such relations
  
• [My own deduction] "Categorization circuitry" is essentially what is needed to build a computer capable of composition
  
• A soloist draws upon a vocabulary of sounds a phrases that comprise a musical language
  
• In terms of improvisation, a brain can't generate complex, far-reaching structures enough to improvise a piece of significant depth [but perhaps a computer can?]
  
• Mozart mapped out the structure of his compositions before filling in the details (this is great news, because it's how my program is designed! So at least I know this method is workable!)
• Scores can limit the capacity of composers (this again is good news: my program is not bounded by traditional scoring)
• Intelligence comes from neural networks
  
• "It is memory that is the composer's workshop"
  
• "The phenomenon of musical ideas arriving full-blown in the composer's mind is called inspiration"
• "[The soloist] works from a vocabulary of sounds, and a kind of grammar for juxtaposing them, that has become his musical language"
• "Musicians work through a hierarchy of ready-made movements. Thousands of patterns of scales and arpeggios and chord progressions are deeply channeled in their nervous system"
• "[Mozart] began by mapping a composition's structure. Only later did he go back to fill in supporting voices and embellishments that could be written in any number of ways without changing the basic character of the piece"
• "Music notation tends to discourage complex melodies and rhythms"
• "By promoting abstracted, hierarchical thinking, the score can seduce composers into a theoretical, unmusical approach to composition"
• "In the end, intellectual power of any kind arises from the laborious creation of networks of neurons"
  

These constitute the notes I took on my reading today.

Music, the Brain, and Ecstasy

Music, the Brain, and Ecstasy
Chapter 5: Rhythm

• Meter vs. Phrasing
• Phrasing is a higher-level unit 0f perception than meter, and encompasses harmonic tension, contour, and dynamics
  
• Pulse lies at the core of meter
  
• Perception of meter is based on prime numbers
• Polyrhythms are made by playing more than one meter at a time
• Syncopation is created when beats are accentuated apart from the regular metrical pattern; often the offbeats are regular enough to anticipate
• Memory vs. Anticipation
• Memory recalls what has already happened, anticipation draws on memory to predict notes to come (usually only a beat or two in the future)
• Importance of tempo: if music moves too slowly, the relations are not close enough to be intelligible; if music moves too quickly, the brain cannot keep up with the relation modeling and has to move to shallower relations, missing the nuances of the piece
• Music needs some gradual changes in tempo; sounds unnatural without them
• Harmonic complexity vs. Metrical Complexity have an inverse relationship
• Most listeners and composers alike now opt for harmonic complexity since harmony information is parallel, while metric information is serial, thus more harmony information can be modeled in a shorter time
  
• "Memory is music's canvas"
  
• "In music, it is phrasing that reaches farthest across time to encompass the deepest relations"
• "Composers gain maximum effect by interweaving the tensions created by music's various aspects"
• "Tempo matters because the mechanics of music perception are exceedingly sensitive to the rate at which musical structures are presented to the brain"
• "Most tempo fluctuations are made intentionally. Music just doesn't sound right without them"
• "The more harmony wanders from its tonal center, the more it requires rhythmic buttressing"
  

These constitute the notes I took on my reading today.

Music, the Brain, and Ecstasy

Music, the Brain, and Ecstasy
Chapter 4: Harmony

• Harmony is essentially the "depth" dimension of music
• Dissonance is greater between lower notes and it is for this reason that bass notes should be well-spaced
• The effect or "feeling" of a chord depends mostly on its context within a larger harmonic progression, not solely upon the identity of the chord
• Notes 1, 3, 4, and 5 in a scale tend to appear more in musical phrases, especially in positions of emphasis
• "Triads are at the heart of the harmony we are accustomed to"
• "Western music is built on variations of a few dozen standard progressions"
• Harmony is all about offsets - relations between notes and chords, not the identity of individual members
• A group of composers known as serialists, including Arnold Schoenberg, Béla Bartók, and Igor Stravinsky tried discarding tonal centers (thus effectively removing harmony), resulting in a kind of atonal music that few listeners could grasp and even fewer enjoyed
  

These constitute the notes I took on my reading today.