A content selection system and method for identifying and organizing moods in content using objectively measured scores for rhythm, texture and pitch (RTP) and clustered into six mood classifications based on an objective analysis of the measured scores. Digitized representations of the content may also be identified and organized based on the content's frequency data, three-dimensional shapes derived from the digitized representations, and colors derived from the frequency data. Each piece of content may be identified by at least a mood shape, but may also be identified by a mood color and/or a mood based on the clustered RTP scores and/or the digitized representation. Users of the selection system may be able to view the moods identified in the different manners, or combinations of two or three mood identifying manners and select and organize content based on the identified moods.

The present invention relates to a system and a method for selecting an audio file using motion data from a mobile computing device connected to or held by a user, the mobile computing device comprising or coupled to motion sensors. The method comprising steps of moving the mobile computing device, obtaining motion data from the motion sensors, computing from the motion data step data based on a number of steps taken by the user in a specific period of time, computing a metronome beat based on the step data and generating a metronome beat file, selecting a stored audio file having a predefined beat parameter matching the metronome beat of the metronome beat file, and playing the audio file. The present invention provides a technology solution delivered through a mobile computing device, such as smart phone, or other computing device, such as a laptop or a PC, a wrist or smart watch, or an accelerometer, pedometer or other external computing device having computer processor means, that improves the gait of people with Parkinson's disease. In use, the user's daily mobility is assessed through application software on a mobile computing device which is operable to calculate a required individually prescribed treatment for a user. The treatment is then delivered through speakers of the mobile computing device in the form of metronome therapy which is form of auditory cueing that is used to treat people with Parkinson's disease.

The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.

Disclosed is a platform enabling users to generate animations synchronized to a musical track in an app-based environment which facilitates collaboration. A method of generating such animations involves first receiving, by a host device executing an app input data from one or more input devices. The app utilizes a layers module to assign the input data to one or more layers. The app assigns input data to layers and allows modification of inputs and timestamps of the input data. The app further allows application of one or more media assets to the inputs. Users of the platform may each execute the app, or execute a companion app that allow communication to the host device. The app may also facilitate compiling the one or more layers into a musical animation file. The musical animation file may store the one or more layers and metadata identifying the musical track.

The invention generally pertains to a hand-held computing device. More particularly, the invention pertains to a computing device that is capable of controlling the speed of the music so as to affect the mood and behavior of the user during an activity such as exercise. By way of example, the speed of the music can be controlled to match the pace of the activity (synching the speed of the music to the activity of the user) or alternatively it can be controlled to drive the pace of the activity (increasing or decreasing the speed of the music to encourage a greater or lower pace). One aspect of the invention relates to adjusting the tempo (or some other attribute) of the music being outputted from the computing device. By way of example, a songs tempo may be increased or decreased before or during playing.

The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting, from among a collection of videos, a set of candidate videos that (i) are identified as being associated with a particular song, and (ii) are classified as a cappella video recordings; extracting, from each of the candidate videos of the set, a monophonic melody line from an audio channel of the candidate video; selecting, from among the set of candidate videos, a subset of the candidate videos based on a similarity of the monophonic melody line of the candidate videos of the subset with each other; and providing, to a recognizer that recognizes songs from sounds produced by a human voice, (i) an identifier of the particular song, and (ii) one or more of the monophonic melody lines of the candidate videos of the subset.

The present invention relates to an apparatus and method for identifying music in a content, The present invention includes extracting and storing a fingerprint of an original audio in an audio fingerprint DB; extracting a first fingerprint of a first audio in the content; and searching for a fingerprint corresponding to the fingerprint of the first audio in the audio fingerprint DB, wherein the first audio is audio data in a music section detected from the content.

A collaborative cloud-based digital music composition, performance and production studio system network employing machine-intelligent digital audio workstation (DAW) systems that are supported by cloud-based automated music composition, performance, production and publishing services. Such services enable improved workflows and enhanced productivity, while ensuring that the music IP rights of all parties involved in the AI-assisted music creation process are respected and responsibly managed in the best economic interests of individual artists, performers, producers, publishers and consumers alike. The digital music studio system network can be realized in various ways supporting the DAW systems in ways suited to different user preferences and application environments.

The present invention relates to a method and system for analysing audio (eg. music) tracks. A predictive model of the neuro-physiological functioning and response to sounds by one or more of the human lower cortical, limbic and subcortical regions in the brain is described. Sounds are analysed so that appropriate sounds can be selected and played to a listener in order to stimulate and/or manipulate neuro-physiological arousal in that listener. The method and system are particularly applicable to applications harnessing a biofeedback resource.