A system, method and computer product for combining audio tracks. In one example embodiment herein, the method comprises determining at least one music track that is musically compatible with a base music track, aligning those tracks in time, and combining the tracks. In one example embodiment herein, the tracks may be music tracks of different songs, the base music track can be an instrumental accompaniment track, and the at least one music track can be a vocal track. Also in one example embodiment herein, the determining is based on musical characteristics associated with at least one of the tracks, such as an acoustic feature vector distance between tracks, a likelihood of at least one track including a vocal component, a tempo, or musical key. Also, determining of musical compatibility can include determining at least one of a vertical musical compatibility or a horizontal musical compatibility among tracks.

An electronic device segments a first and second MIDI files into pluralities of source segments and target segments. For each of a plurality of consecutive pairs of first and second target segments, the electronic device identifies a first source segment corresponding to the first target segment of the consecutive pair and identifies a second source segment corresponding to the second target segment of the consecutive pair, where the first and second source segments are identified by determining that the first and second source segments are harmonically conformant to the corresponding first and second target segments, and determining that a transition between the first and second source segments is graphically conformant to a transition between a consecutive pair of source segments. The electronic device generates a third MIDI file using the identified first and second source segments for each of the plurality of consecutive pairs of first and second target segments.

Embodiments described herein relate to techniques of coordinating sensory event timelines of multiple devices. The devices may use the sensory even timelines to output sensory events such as audio segments. The devices may take turns determining the sensory events to be output by the devices using their sensory event timelines. The techniques coordinate transitions of the devices between a first mode in which a device is allowed to determine sensory events to be output and a second mode in which a device outputs sensory events determined by another device.

Systems and methods for providing audio-file loop-playback functionality are provided. The system includes a processor that performs a method including setting a playback loop start-point based on a first selection of a button; setting a loop end-point, associating a loop with an audio file, and entering into the loop based on a second selection of the button; and exiting the loop based on a third selection of the button. Associating the loop with the audio file includes adding metadata to the audio file. The metadata associates the loop with a button. The method includes reentering the loop based on a fourth selection of the button and exiting the loop based on a fifth selection of the button.

The present invention relates to a computer implemented system and method for generating an audio output file. The method including using one or more processors to perform steps of: receiving audio tracks, each audio track created according to audio parameters; separating each audio track into at least one selectable audio block, each audio block including audio content from a musical instrument involved in creating the audio track; assigning a unique identifier to each audio block; using the unique identifiers to select audio blocks, and generating the audio output by combining the audio blocks. The present invention prevents the use of the same combination of audio blocks in the generation of audio output to ensure that the audio output files generated a sufficiently unique. Also provided are audio file recording, editing and mixing modules enabling a user to have full creative control over mix and other parameters to modify as desired the audio file generated.

According to a first embodiment, there is presented herein a method of increasing the energy level of a user-selected song in a loop-based music generation system. In one embodiment the algorithm is integrated into a music generation/song construction process and comprises of three different approaches, with one of the three being a hybrid version of the remaining approaches.

Scalable similarity-based generation of compatible music mixes. Music clips are projected in a pitch interval space for computing musical compatibility between the clips as distances or similarities in the pitch interval space. The distance or similarity between clips reflects the degree to which clips are harmonically compatible. The distance or similarity in the pitch interval space between a candidate music clip and a partial mix can be used to determine if the candidate music clip is harmonically compatible with the partial mix. An indexable feature space may be both beats-per-minute (BPM)-agnostic and musical key-agnostic such that harmonic compatibility can be quickly determined among potentially millions of music clips. A graphical user interface-based user application allows users to easily discover combinations of clips from a library that result in a perceptually high-quality mix that is highly consonant and pleasant-sounding and reflects the principles of musical harmony.

Vehicle machine learning methods include providing one or more computer processors communicatively coupled with a vehicle. Using data gathered from biometric sensors and/or vehicle sensors, a machine learning model is trained to determine a mental state of a driver and/or a driving state corresponding with a portion of a trip. In implementations the mental or driving state may be determined without a machine learning model. Based at least in part on the determined mental state and the determined driving state, one or more interventions are automatically initiated to alter the mental state of the driver. The interventions may include preparing (or modifying) and initiating a music playlist, altering a lighting condition within the vehicle, altering an audio condition within the vehicle, altering a temperature condition within the vehicle, and initiating, altering, or withholding conversation from a conversational agent. Vehicle machine learning systems perform the vehicle machine learning methods.

A method of making audio music selection and creating a mixtape, comprising importing song files from a song repository; sorting and filtering the song files based on selection criteria; and creating the mixtape from the song files sorting and filtering results. The sorting and filtering of the song files comprise: spectral analyzing each of the song files to extract low level acoustic feature parameters of the song file; from the low level acoustic feature parameter values, determining the high level acoustic feature parameters of the analyzed song file; determining a similarity score of each of the analyzed song files by comparing the acoustic feature parameter values of the analyzed song file against desired acoustic feature parameter values determined from the selection criteria; and sorting the analyzed song files according to their similarity scores; and filtering out the analyzed song files with first similarity scores lower than a filter threshold.

A method for processing music audio data, including providing input audio data representing a first piece of music comprising a mixture of musical timbres. The method also includes decomposing the input audio data to generate at least first-timbre decomposed data representing a first timbre selected from the musical timbres of the first piece of music, and second-timbre decomposed data representing a second timbre selected from the musical timbres of the first piece of music. The method also includes applying a transport control to obtain transport controlled first-timbre decomposed data. The method also includes recombining audio data obtained from the transport controlled first-timbre decomposed data with audio data obtained from the second-timbre decomposed data to obtain recombined audio data.