The purpose of the present invention is to provide a system capable of analyzing intuitively-created improvisation performances without relying on music theories. There is provided an improvisation performance analysis system, comprising: a music information coding section 10 for analyzing and coding music data of an improvisation performer stored in a music storage medium; a tone sequence pattern extraction section 11 for extracting all of first- to n-th-order tone sequence patterns which are likely to occur as n-th Markov chains in order to perform a stochastic analysis with a Markov model using the coded music data; a pitch transition sequence extraction section 12 for obtaining a pitch transition sequence for each of the extracted tone sequence patterns; a transition probability/appearance probability calculation section 13 for using the Markov model to calculate a transition probability of each pitch transition sequence and an appearance probability of each transition sequence at each of the first- to n-th-order hierarchical levels; and an improvisation performance phrase structuring section 14 for rearranging the pitch transition probabilities at each hierarchical level based on the transition probabilities and the appearance probabilities, identifying pitch transition sequences which are statistically likely to occur and expressing the pitch transition sequences in all keys as music scores based on the twelve-tone equal temperament to thereby generate improvisation performance phrases.

A generative composition system reduces existing musical artefacts to constituent elements termed Form Atoms. To provide myriad new composition, a set of heuristics ensure that musical textures between concatenated musical sections follow a supplied and defined briefing narrative for the new composition whilst contiguous concatenated Form Atoms are also automatically selected to see that similarities in respective and identified attributes of musical textures for those musical sections are maintained to support maintenance of musical form. Independent aspects of the disclosure further ensure that, within the composition work, such as a media product or a real-time audio stream, chord spacing determination and control practiced to maintain musical sense in the new composition. Further, a structuring of primitive heuristics operates to maintain pitch and permit key transformation. The system and its functionality provides signal analysis and music generation through allowing emotional connotations to be specified and reproduced from cross-referenced Form-Atoms.

Music data memory includes pieces of music within a group and other pieces of music outside the group. The next piece to be played is automatically determined by random table among pieces within the group. Favorite or newest piece is weighted to be more frequently played in the group. Piece in music data memory is automatically included into the group by random table. Newly downloaded piece into music data memory is included into the group by priority. Most frequently played piece is excluded from the group in place of newly included piece. Favorite or newest piece may be an exception of exclusion. Next piece is capable of being played in tempo similar to that of preceding piece by means of tempo-adjusted or piece replacement or repetition of the same piece for the purpose of continued baby cradling in synchronism with the same tempo of succeeding pieces.

The purpose of the present invention is to provide a system capable of analyzing intuitively-created improvisation performances without relying on music theories. There is provided an improvisation performance analysis system, comprising: a music information coding section 10 for analyzing and coding music data of an improvisation performer stored in a music storage medium; a tone sequence pattern extraction section 11 for extracting all of first- to n-th-order tone sequence patterns which are likely to occur as n-th Markov chains in order to perform a stochastic analysis with a Markov model using the coded music data; a pitch transition sequence extraction section 12 for obtaining a pitch transition sequence for each of the extracted tone sequence patterns; a transition probability/appearance probability calculation section 13 for using the Markov model to calculate a transition probability of each pitch transition sequence and an appearance probability of each transition sequence at each of the first- to n-th-order hierarchical levels; and an improvisation performance phrase structuring section 14 for rearranging the pitch transition probabilities at each hierarchical level based on the transition probabilities and the appearance probabilities, identifying pitch transition sequences which are statistically likely to occur and expressing the pitch transition sequences in all keys as music scores based on the twelve-tone equal temperament to thereby generate improvisation performance phrases.

Music data memory includes pieces of music within a group and other pieces of music outside the group. The next piece to be played is automatically determined by random table among pieces within the group. Favorite or newest piece is weighted to be more frequently played in the group. Piece in music data memory is automatically included into the group by random table. Newly downloaded piece into music data memory is included into the group by priority. Most frequently played piece is excluded from the group in place of newly included piece. Favorite or newest piece may be an exception of exclusion. Next piece is capable of being played in tempo similar to that of preceding piece by means of tempo-adjusted or piece replacement or repetition of the same piece for the purpose of continued baby cradling in synchronism with the same tempo of succeeding pieces.

Music data memory includes pieces of music within a group and other pieces of music outside the group. The next piece to be played is automatically determined by random table among pieces within the group. Favorite or newest piece is weighted to be more frequently played in the group. Piece in music data memory is automatically included into the group by random table. Newly downloaded piece into music data memory is included into the group by priority. Most frequently played piece is excluded from the group in place of newly included piece. Favorite or newest piece may be an exception of exclusion. Next piece is capable of being played in tempo similar to that of preceding piece by means of tempo-adjusted or piece replacement or repetition of the same piece for the purpose of continued baby cradling in synchronism with the same tempo of succeeding pieces.

A method and system for analyzing patterns in the relationships of notes of an input piece of music. The method comprises generating a set of the most frequently occurring note pitches in ascending pitch order that matches an interval pattern, and detecting out-of-key pitches that lie outside of this internal pattern. One or more potential key sequence bifurcations are identified which represent a list of possible key sequences according to forwards and backwards analysis. By finding patterns of repetition in the chordal sequences that may be generated according to these key sequence bifurcations, a key sequence that allows the most frequently recurring chord sequences may be chosen. Chord sequences may be analyzed by using ghost chords, temporary harmonic structures that are created, updated and finalized over time according to a combination of essential and inessential note fragments. The method further comprises identifying non-harmony pitches according to the analyzed chord sequence.

A method and system for analyzing patterns in the relationships of notes of an input piece of music. The method comprises generating a set of the most frequently occurring note pitches in ascending pitch order that matches an interval pattern, and detecting out-of-key pitches that lie outside of this interval pattern. One or more potential key sequence bifurcations are identified which represent a list of possible key sequences according to forwards and backwards analysis. By finding patterns of repetition in the chordal sequences that may be generated according to these key sequence bifurcations, a key sequence that allows the most frequently recurring chord sequences may be chosen. Chord sequences may be analyzed by using ghost chords, temporary harmonic structures that are created, updated and finalized over time according to a combination of essential and inessential note fragments. The method further comprises identifying non-harmony pitches according to the analyzed chord sequence.

Music data memory includes pieces of music within a group and other pieces of music outside the group. The next piece to be played is automatically determined by random table among pieces within the group. Favorite or newest piece is weighted to be more frequently played in the group. Piece in music data memory is automatically included into the group by random table. Newly downloaded piece into music data memory is included into the group by priority. Most frequently played piece is excluded from the group in place of newly included piece. Favorite or newest piece may be an exception of exclusion. Next piece is capable of being played in tempo similar to that of preceding piece by means of tempo-adjusted or piece replacement or repetition of the same piece for the purpose of continued baby cradling in synchronism with the same tempo of succeeding pieces.

A method and system for analyzing patterns in the relationships of notes of an input piece of music. The method comprises generating a set of the most frequently occurring note pitches in ascending pitch order that matches an interval pattern, and detecting out-of-key pitches that lie outside of this interval pattern. One or more potential key sequence bifurcations are identified which represent a list of possible key sequences according to forwards and backwards analysis. By finding patterns of repetition in the chordal sequences that may be generated according to these key sequence bifurcations, a key sequence that allows the most frequently recurring chord sequences may be chosen. Chord sequences may be analyzed by using ghost chords, temporary harmonic structures that are created, updated and finalized over time according to a combination of essential and inessential note fragments. The method further comprises identifying non-harmony pitches according to the analyzed chord sequence.