The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.

A music piece analyzer includes: a beat interval acquiring unit configured to acquire a beat interval in music piece data; a candidate detector configured to detect sounding positions where a change amount for sounding is equal to or more than a predetermined threshold in the music piece data, as candidates for sounding positions of a snare drum; and a sounding position determination unit configured to determine that the candidates for the sounding positions at a two-beat interval acquired by the beat interval acquiring unit in the music piece data are the sounding positions of the snare drum, among the candidates for the sounding positions of the snare drum.

A control method includes receiving a detection result relating to a first event in a performance; changing a following degree in a middle of the performance to which a second event in the performance follows the first event; and determining an operating mode of the second event based on the following degree.

A music piece development analyzer includes: a comparison target sound detector configured to detect a sound production position of a comparison target sound in a form of a sound of a predetermined musical instrument from music piece data; a sound production pattern comparing unit configured to set at least two comparison sections each having a predetermined length in the music piece data, compare the at least two comparison sections in terms of a sound production pattern of the comparison target sound, and detect a similarity degree of the sound production pattern between the at least two comparison sections, and a development change-point determining unit configured to determine a development change-point of the music piece data based on the similarity degree.

A resonance sound signal generation device comprises a designation receiver that receives designation of a pitch, a sound signal instructor that provides an instruction for generating a sound signal corresponding to the designated pitch, a producer that produces a resonance sound signal representing a resonance sound based on a plurality of pitches, a determiner that determines whether another pitch is designated at a time of designation of one pitch, and a resonance sound instructor that instructs the producer to produce a resonance sound signal of the one pitch and a resonance sound signal of the another pitch based on the one pitch and the another pitch when determination is made that the another pitch is designated at the time of designation of the one pitch, and does not instruct the producer to produce resonance sound signals when determination is made that the another pitch is not designated at the time of designation of the one pitch.

A controller for real-time visual display of music includes a music analysis module and a display control module. The music analysis module receives an audio input, determines human perceived musical structures, human felt affect and emotion as a function of the audio input, and outputs a signal corresponding to the determined structure, affect and emotion. The display control module is operatively coupled to the music analysis module and receives the signal and controls a visual display as a function thereof to express the determined musical structure, affect and emotion in a visual manner.

A method of generating a musical score file for one or more target musical instruments with a score generation component based on input audio data. The score generation component finds candidate musical notes within the input audio data using a frequency analysis to identify segments that share substantially the same audio frequency, and finds a best match for those candidate musical notes in audio data associated with target musical instruments in a sound database. A generated musical score file can be printed as sheet music or audibly played back over speakers.

The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.

A method for processing a voice signal by an electronic system to create a song is disclosed. The method comprises the steps in the electronic system of acquiring an input singing voice recording (11); estimating a musical key (15b) and a Tempo (15a) from the singing voice recording (11); defining a tuning control (16) and a timing control (17) able to align the singing voice recording (11) with the estimated musical key (15b) and Tempo (15a); applying the tuning control (16) and the timing control (17) to the singing voice recording (11) so that an aligned voice recording (20) is obtained. Next, the method comprises the step of generating an music accompaniment (23) as function of the estimated musical key (15b) and Tempo (15a) and an arrangement database (22) and mixing the aligned voice recording (20) and the music accompaniment (23) to obtain the song (12). A system a server and a device are also disclosed.

Apparatus and associated methods relate to comparing a musical score model to a captured performance of the musical score, calculating a degree of similarity between the musical score model and the captured performance based on the comparison, and automatically evaluating the captured performance based on the degree of similarity and musical score degree of difficulty determined as a function of the musical score entropy. In an illustrative example, a musician may be learning to play the musical score. The musical score may be modelled, for example, based on pitch, volume, and rhythm, permitting comparison to the captured performance of the musical score. In some examples, the musical score degree of difficulty may be adapted based on the captured performance evaluation. Some embodiments may generate musical scores based on the captured performance evaluation. Various examples may advantageously provide corrective instruction based on the degree of difficulty and the captured performance evaluation.