Computing devices and methods for providing a music customization graphical user interface (GUI) to a user computing device are disclosed. The music customization GUI comprises song name selectors that each correspond to a different song and a music player region that includes a song customization selector. A customization window comprises music stem indicators that each correspond to at least one music stem of a selected song. The customization window also comprises mixing buttons that include a first mixing button configured to add a corresponding music stem to a user song mix, and a second mixing button configured to remove the music stem from the user song mix. A download button is configured to download a file comprising the user song mix to a user computing device.

Indications of sample machine learning models which create synthetic content items are provided via programmatic interfaces. A representation of a synthetic content item produced by one of the sample models in response to input obtained from a client of a provider network is presented. In response to a request from the client, a machine learning model is trained to produce additional synthetic content items.

An electronic-drum module for connection to one or more electronic-drum pads is provided. The module includes an electronic display; a first memory storing audio files for playback when the playback is triggered by a signal received from a pad; and one or more processors coupled to the display and the memory. The processors are configured receive an instruction to transfer a set of samples. The set of samples is associated with a priority-instruction and includes a first subset of samples and a second subset of samples. The processors are also configures to transfer the first subset of samples from a second memory to the first memory based on the priority-instruction before transferring the second subset of samples and to transfer the second subset of samples from the second memory to the first memory.

A method for processing information, terminal device and a computer storage medium are disclosed. The method for processing information includes that: a first control instruction is acquired, and a first application is switched to a preset mode according to the first control instruction; a first triggering operation is acquired based on the preset mode, at least two pieces of multimedia data are selected based on the first triggering operation, and a first playing interface is generated; when a second control instruction is acquired, the at least two pieces of multimedia data in the first playing interface are sequentially played; in a process of playing first multimedia data in the at least two pieces of multimedia data, first audio data is acquired; and the first multimedia data and the first audio data are synthesized as second multimedia data.

User interface techniques provide user vocalists with mechanisms for seeding subsequent performances by other users (e.g., joiners). A seed may be a full-length seed spanning much or all of a pre-existing audio (or audiovisual) work and mixing, to seed further contributions of one or more joiners, a user's captured media content for at least some portions of the audio (or audiovisual) work. A short seed may span less than all (and in some cases, much less than all) of the audio (or audiovisual) work. For example, a verse, chorus, refrain, hook or other limited “chunk” of an audio (or audiovisual) work may constitute a seed. A seeding user's call invites other users to join the full-length or short-form seed by singing along, singing a particular vocal part or musical section, singing harmony or other duet part, rapping, talking, clapping, recording video, adding a video clip from camera roll, etc. The resulting group performance, whether full-length or just a chunk, may be posted, livestreamed, or otherwise disseminated in a social network.

Indications of sample machine learning models which create synthetic content items are provided via programmatic interfaces. A representation of a synthetic content item produced by one of the sample models in response to input obtained from a client of a provider network is presented. In response to a request from the client, a machine learning model is trained to produce additional synthetic content items.

A system for platform-independent visualization of audio content, in particular audio tracks utilizing a central computer system in communication with user devices via a computer network. The central system utilizes various algorithms to identify spoken content from audio tracks and selects visual assets associated with the identified content. Thereafter, a visualized audio track is available for users to listen and view. Audio tracks, for example Podcasts, may be segmented into topical audio segments based upon themes or topics, with segments from disparate podcasts combined into a single listening experience, based upon certain criteria, e.g., topics, themes, keywords, and the like.

A specialized audio/instrument cable with built-in digital signal processing capabilities that adds digital audio sampling capabilities that allows the user to trigger synthesized sounds or virtual musical instruments from within the cable itself to affect the sound generated from an instrument or microphone such that the cable is the only connection needed between the instrument or microphone and an output device. Using voice recognition, the specialized cable can select an audio effects chain algorithm and/or sampled sound algorithm extrapolated from a musical digital audio fingerprint (MDAF) created from a desired musician's instrument to alter the sound of the input instrument's audio.

A pedal device receives a connection signal transmitted from headphone to establish first communication that is communication with the headphone. Then, in a case where the first communication has been established, the pedal device transmits the connection signal including information indicating that communication with the headphone has been established. By receiving the connection signal from the pedal device, a portable terminal establishes second communication that is communication with the pedal device. In a case where the received connection signal includes information that the communication with the headphone has been established, the portable terminal may determine that communication establishment between the pedal device and the headphone has been completed.

Disclosed herein are computer-implemented method, computer-readable storage medium, and DAW embodiments for implementing a music composition aid. An embodiment includes retrieving a first constraint value, receiving a selection of a set of musical elements, and accepting a second constraint value corresponding to the set of musical elements. Some embodiments further include invoking an iterator function, using at least the second constraint value as an argument, and generating an output of the iterator function, limiting a size of the output of the iterator function, according to the lesser of the first constraint value or a transform of the second constraint value. Output of the iterator function may include, of the set of musical elements, a subset determined by the second constraint value. The size of the output may be no more than the first constraint value. Further embodiments may render the output of the iterator function visually and/or audibly, for example.