A method of converting a frame of a voice sample to a singing frame includes obtaining a pitch value of the frame; obtaining formant information of the frame using the pitch value; obtaining aperiodicity information of the frame using the pitch value; obtaining a tonic pitch and chord pitches; using the formant information, the aperiodicity information, the tonic pitch, and the chord pitches to obtain the singing frame; and outputting or saving the singing frame.

The present systems, devices, and methods generally relate to generating families of symbol sequences with controllable degree of correlation within and between them using quantum computers, and particularly to the exploitation of this capability to generate families of symbol sequences representing musical events such as, but not limited to, musical notes, musical chords, musical percussion strikes, musical time intervals, musical note intervals, and musical key changes that comprise a musical composition. Quantum random walks on graphs representing allowed transitions between musical events are also employed in some implementations.

Systems, devices, and methods for segmenting musical compositions are described. Discrete, musically-coherent segments (such as intro, verse, chorus, bridge, solo, and the like) of a musical composition are identified. Distance measures are used to evaluate whether each bar of a musical composition is more like the bars that directly precede it or more like the bars that directly succeed it, and each respective series of musically similar bars is assigned to the same respective segment. Large changes in the distance measure(s) between adjacent bars may be used to identify boundaries between abutting musical segments.

Computer systems and computer program products for implementing segmentation are also described. The results of segmentation may advantageously be applied in computer-based composition of music and musical variations, as well as in other applications involving labelling, characterizing, or otherwise processing music.

Systems, devices, and methods for segmenting musical compositions are described. Discrete, musically-coherent segments (such as intro, verse, chorus, bridge, solo, and the like) of a musical composition are identified. Distance measures are used to evaluate whether each bar of a musical composition is more like the bars that directly precede it or more like the bars that directly succeed it, and each respective series of musically similar bars is assigned to the same respective segment. Large changes in the distance measure(s) between adjacent bars may be used to identify boundaries between abutting musical segments. Computer systems and computer program products for implementing segmentation are also described. The results of segmentation may advantageously be applied in computer-based composition of music and musical variations, as well as in other applications involving labelling, characterizing, or otherwise processing music.

A dual sound source audio data processing method and apparatus are provided. The method includes obtaining audio data of a song pair including a first song and a second song, the first and second songs having a same accompaniment audio but different voice audio. The audio data is decoded to obtain first mono audio data corresponding to the first song and second mono audio data corresponding to the second song. The first and second mono audio data are combined to one piece of two-channel audio data including a left audio channel and a right audio channel. A play time of the two-channel audio data is divided into play periods, and energy suppression is selectively performed on the left audio channel and the right audio channel in different play periods.

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.

Embodiments of the present invention relate to automatically identifying structures of a music stream. A segment structure may be generated that visually indicates repeating segments of a music stream. To generate a segment structure, a feature that corresponds to a music attribute from a waveform corresponding to the music stream is extracted from a waveform, such as an input signal. Utilizing a signal segmentation algorithm, such as a Variable Markov Oracle (VMO) algorithm, a symbolized signal, such as a VMO structure, is generated. From the symbolized signal, a matrix is generated. The matrix may be, for instance, a VMO-SSM. A segment structure is then generated from the matrix. The segment structure illustrates a segmentation of the music stream and the segments that are repetitive.

A chord identification method selects from among a plurality of chord identifiers a chord identifier that corresponds to an attribute of a piece of music represented by an audio signal, where the plurality of chord identifiers corresponds to respective ones of a plurality of attributes relating to pieces of music; and identifies a chord for the audio signal by applying a feature amount of the audio signal to the selected chord identifier.

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.

Embodiments of the present invention relate to automatically identifying structures of a music stream. A segment structure may be generated that visually indicates repeating segments of a music stream. To generate a segment structure, a feature that corresponds to a music attribute from a waveform corresponding to the music stream is extracted from a waveform, such as an input signal. Utilizing a signal segmentation algorithm, such as a Variable Markov Oracle (VMO) algorithm, a symbolized signal, such as a VMO structure, is generated. From the symbolized signal, a matrix is generated. The matrix may be, for instance, a VMO-SSM. A segment structure is then generated from the matrix. The segment structure illustrates a segmentation of the music stream and the segments that are repetitive.