Computer-based systems, devices, and methods for generating musical compositions are described. A population of musical compositions stored in digital media are each segmented to produce abridged samples. The samples are analyzed to identify “parent” compositions that best exhibit or evoke a particular desired quality. The parent compositions are cross-bred to generate a set of child compositions which are similarly segmented and analyzed. The child compositions that best exhibit or evoke the particular desired quality are re-cast as parent compositions from which another generation of child compositions are bred. Mutations in the form of musical variations are inserted in at least some iterations and the process is repeated until at least one child composition that satisfies some exit criterion is returned.

Computer-based systems, devices, and methods for generating musical note sequences are described. One or more musical composition(s) stored in digital media include one or more data object(s) that encode notes and/or note sequences. At least one note sequence is processed to form a time-ordered sequence of parallel notes, which is analyzed to determine a k-back probability transition matrix for the at least one note sequence. An attribute, such as a style, of the at least one note sequence is thus encoded and used to generate new note sequences that embody a similar attribute or style. In some implementations, the at least one note sequence may include a concatenated set of note sequences representative of a particular library of musical compositions.

A system and method for estimating the popularity of song by calculating the (absolute and/or contrastive) harmonic surprise of each song in a corpus of music data, determining the popularity of each song in the corpus (e.g., based on a music chart, downloads, online streams), determining correlations between harmonic surprise and popularity, and estimating the popularity of an individual song based on the (absolute and/or contrastive) harmonic surprise of the individual song and the correlations between harmonic surprise and popularity.

An electronic apparatus, including a memory configured to store a first artificial intelligence model; and a processor connected to the memory and configured to: based on receiving an input audio signal, obtain an input frequency spectrum image representing a frequency spectrum of the input audio signal, input the input frequency spectrum image to the first artificial intelligence model, obtain an output frequency spectrum image from the first artificial intelligence model, obtain an output audio signal based on the output frequency spectrum image, wherein the first artificial intelligence model is trained based on a target learning image, and wherein the target learning image represents a target frequency spectrum of a specific style, and is obtained from a second artificial intelligence model based on a random value.

A cuepoint determination system utilizes a convolutional neural network (CNN) to determine cuepoint placements within media content items to facilitate smooth transitions between them. For example, audio content from a media content item is normalized to a plurality of beats, the beats are partitioned into temporal sections, and acoustic feature groups are extracted from each beat in one or more of the temporal sections. The acoustic feature groups include at least downbeat confidence, position in bar, peak loudness, timbre and pitch. The extracted acoustic feature groups for each beat are provided as input to the CNN on a per temporal section basis to predict whether a beat immediately following the temporal section within the media content item is a candidate for cuepoint placement. A cuepoint placement is then determined from among the candidate cuepoint placements predicted by the CNN.

A cuepoint determination system utilizes a convolutional neural network (CNN) to determine cuepoint placements within media content items to facilitate smooth transitions between them. For example, audio content from a media content item is normalized to a plurality of beats, the beats are partitioned into temporal sections, and acoustic feature groups are extracted from each beat in one or more of the temporal sections. The acoustic feature groups include at least downbeat confidence, position in bar, peak loudness, timbre and pitch. The extracted acoustic feature groups for each beat are provided as input to the CNN on a per temporal section basis to predict whether a beat immediately following the temporal section within the media content item is a candidate for cuepoint placement. A cuepoint placement is then determined from among the candidate cuepoint placements predicted by the CNN.

A lyrics analyzer generates tags and explicitness indicators for a set of tracks. These tags may indicate the genre, mood, occasion, or other features of each track. The lyrics analyzer does so by generating an n-dimensional vector relating to a set of topics extracted from the lyrics and then using those vectors to train a classifier to determine whether each tag applies to each track. The lyrics analyzer may also generate playlists for a user based on a single seed song by comparing the lyrics vector or the lyrics and acoustics vectors of the seed song to other songs to select songs that closely match the seed song. Such a playlist generator may also take into account the tags generated for each track.

An optical head assembly for sue with a stringed musical instrument, the vibrations of the strings causing a light beam to be modulated in accordance with the frequency of the vibrating strings. The modulated light output, produced by the relative motion between two adjacent grates, is coupled to a device with converts the modulated light beam to a corresponding modulated electrical signal which, in turn, is coupled to an amplifier associated with the instrument.

An optical head assembly for use with a stringed musical instrument, the vibrations of the strings causing a light beam to be modulated in accordance with the frequency of the vibrating strings. The modulated light output, produced by the relative motion between two adjacent grates, is coupled to a device with converts the modulated light beam to a corresponding modulated electrical signal which, in turn, is coupled to an amplifier associated with the instrument.

A music generation system is provided comprising a processor and a memory operatively coupled to the processor and storing a rhythm template database comprising a plurality of rhythm templates, and a music generation program stored in the memory and executed by the processor to be configured to receive a user input of lyrics, identify a plurality of syllables in the lyrics, determine a syllable pattern in the identified plurality of syllables, match the syllable pattern to a selected rhythm template of the plurality of rhythm templates, generate a melody based on the selected rhythm template, generate a music file encoding the melody and the lyrics, and output the music file encoding the melody and the lyrics.