Patent classifications
G10H2240/135
METHOD AND APPARATUS FOR IDENTIFYING MUSIC IN CONTENT
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.
Method and system for analysing sound
A method and system for analyzing 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 analyzed 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.
Method and system for analysing sound
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.
METHOD AND SYSTEM FOR ANALYSING SOUND
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.
SYSTEMS AND METHODS FOR CLASSIFYING MUSIC FROM HETEROGENOUS AUDIO SOURCES
The disclosed computer-implemented method may include accessing an audio stream with heterogenous audio content; dividing the audio stream into a plurality of frames; generating a plurality of spectrogram patches, each spectrogram patch within the plurality of spectrogram patches being derived from a frame within the plurality of frames; and providing each spectrogram patch within the plurality of spectrogram patches as input to a convolutional neural network classifier and receiving, as output, a classification of music within a corresponding frame from within the plurality of frames. Various other methods, systems, and computer-readable media are also disclosed.
METHOD AND SYSTEM FOR ANALYSING SOUND
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.
Method and system for analysing sound
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.
COMPUTER IMPLEMENTED METHOD INCORPORATING SOCIAL MEDIA NETWORKING FOR THE COLLABORATIVE CREATION, DISTRIBUTION AND CONSUMPTION OF AUDIO MATERIAL
A computer implemented method incorporating social media networking for the collaborative creation, distribution and consumption of audio material. Steps include a processor and database for receiving a plurality of audio files and a non-transitory computer readable medium embodying computer-executable instructions which, when executed by the processor, causes the processor to execute a series of registration, contact and operational tools for facilitating the collaborative creation of music.
Music selection and organization using audio fingerprints
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.
Acoustic fingerprint extraction and matching
A method of acoustic matching of audio recordings by means of acoustic fingerprinting is disclosed. An acoustic fingerprint is extracted from a fragment of an audio recording. The fingerprint represents a highly discriminative compact digital digest (acoustic hash) of the acoustic recording and consists of smaller digital entities called acoustic sub-fingerprints (acoustic hash-words), computed from perceptually essential properties of the acoustic recording. Two acoustic fingerprints corresponding to two audio fragments are matched to determine degree of acoustic similarity of the two audio fragments.