A system and method of creating a personalized sounds and visuals environment to address a person's individual environment and state by receiving output from a plurality of sensors, the sensors detecting the activity of the user and the environment in which the user is active. Sounds and/or visuals to be transmitted to the user for listening and watching on the user's device are determined based on one or more of the sensor outputs, a user profile, a user mode, a user state, and a user context. The determined sounds and/or visuals are transmitted and presented to the user, and the determined sounds and/or visuals are automatically and dynamically modified in real time based on changes in the output from one or more of the plurality of sensors and/or changes in the user's profile.

An adaptive music playback system is disclosed. The system includes a composition system that receives information corresponding to user activity levels. The composition system modifies the composition of a song in response to changes in user activity. The modifications are made according to a set of composition rules to facilitate smooth musical transitions.

A method for controlling a playback tempo of an audio track to be presented at an audio output, the audio track comprising a plurality of audio components, a first audio component of the plurality of audio components being associated with a plurality of sets of audio data, wherein each set of audio data in the plurality of sets of audio data is associated with a respective playback tempo range, the method comprising receiving a playback tempo for presenting the audio track at the audio output, selecting, from the plurality of sets of audio data, a set of audio data that has an associated playback tempo range comprising the received playback tempo, and allocating the selected set of audio data to the first audio component for presenting the audio track at the audio output.

There is provided a signal processing apparatus that includes a control unit that executes, on a basis of a waveform signal generated in accordance with a motion of an attachment portion of a sensor attached to a tool or a body, effect processing for the waveform signal or another waveform signal, the waveform signal being output from the sensor.

The Plant Choir™ system comprises a software program and hardware that measures the electrodermal activity of a person, plant, or animal and translates those readings into music on a computing device. The EDA readings of the individual subjects are translated via the software into musical notes in real time. The creation of the notes is synchronized to a master tempo in order to allow the subjects to play together in a unified fashion similar to a choir. A riff mode allows the subjects to produce multiple notes per beat. The music is rendered using a software synthesis algorithm that employs the pre-recorded sounds of real instruments. The software can also utilize MIDI devices if the operating system has that capability. The software allows the user to load and save their settings so they can create and experiment with their own choir configurations and musical scales.

The Plant Choir™ system comprises a software program and hardware that measures the electrodermal activity of a person, plant, or animal and translates those readings into music on a computing device. The EDA readings of the individual subjects are translated via the software into musical notes in real time. The creation of the notes is synchronized to a master tempo in order to allow the subjects to play together in a unified fashion similar to a choir. A riff mode allows the subjects to produce multiple notes per beat. The music is rendered using a software synthesis algorithm that employs the pre-recorded sounds of real instruments. The software can also utilize MIDI devices if the operating system has that capability. The software allows the user to load and save their settings so they can create and experiment with their own choir configurations and musical scales.

Implementations of the subject matter described herein provide a solution that enables a machine to automatically generate a melody. In this solution, user emotion and/or environment information is used to select a first melody feature parameter from a plurality of melody feature parameters, wherein each of the plurality of melody feature parameters corresponds to a music style of one of a plurality of reference melodies. The first melody feature parameter is further used to generate a first melody that conforms to the music style and is different from the reference melody. Thus, a melody that matches user emotions and/or environmental information may be automatically created.

A system and method of creating a personalized sounds and visuals environment to address a person's individual environment and state by receiving output from a plurality of sensors, the sensors detecting the activity of the user and the environment in which the user is active. Sounds and/or visuals to be transmitted to the user for listening and watching on the user's device are determined based on one or more of the sensor outputs, a user profile, a user mode, a user state, and a user context. The determined sounds and/or visuals are transmitted and presented to the user, and the determined sounds and/or visuals are automatically and dynamically modified in real time based on changes in the output from one or more of the plurality of sensors and/or changes in the user's profile.

A method, computer system, and a computer program product for intelligently synchronizing exercise music for an instructor based group workout is provided. The present invention may include identifying at least one goal workout. The present invention may then include receiving a plurality of verbal cues associated with an instructor and a plurality of nonverbal cues associated with the instructor. The present invention may also include analyzing the received plurality of verbal cues and the received plurality of nonverbal cues. The present invention may further include generating the exercise music based on the analyzed plurality of verbal cues and analyzed plurality of nonverbal cues.

A method includes receiving a non-linguistic input associated with an input musical content. The method also includes, using a model that embeds multiple musical features describing different musical content and relationships between the different musical content in a latent space, identifying one or more embeddings based on the input musical content. The method further includes at least one of: (i) identifying stored musical content based on the one or more identified embeddings or (ii) generating derived musical content based on the one or more identified embeddings. In addition, the method includes presenting at least one of: the stored musical content or the derived musical content. The model is generated by training a machine learning system having one or more first neural network components and one or more second neural network components such that embeddings of the musical features in the latent space have a predefined distribution.