AUDIO CONTENT RECOGNITION METHOD AND SYSTEM
    1.
    发明申请

    公开(公告)号:WO2022146674A1

    公开(公告)日:2022-07-07

    申请号:PCT/US2021/063300

    申请日:2021-12-14

    Abstract: A method implemented by a computing system comprises generating, by the computing system, a fingerprint comprising a plurality of bin samples associated with audio content. Each bin sample is specified within a frame of the fingerprint and is associated with one of a plurality of non-overlapping frequency ranges and a value indicative of a magnitude of energy associated with a corresponding frequency range. The computing system removes. from the fingerprint, a plurality of bin samples associated with a frequency sweep in the andio content.

    MONITORING LOUDNESS LEVEL DURING MEDIA REPLACEMENT EVENT USING SHORTER TIME CONSTANT

    公开(公告)号:WO2020102632A1

    公开(公告)日:2020-05-22

    申请号:PCT/US2019/061632

    申请日:2019-11-15

    Abstract: In one aspect, an example method includes (i) determining, by a playback device, a first loudness level of a first portion of first media content from a first source while the playback device presents the first media content, with the first portion having a first length; (ii) switching, by the playback device, from presenting the first media content from the first source to presenting second media content from a second source; (iii) based on the switching, determining, by the playback device, second loudness levels of second portions of the first media content while the playback device presents the second media content, with the second portions having a second length that is shorter than the first length; and (iv) while the playback device presents the second media content, adjusting, by the playback device, a volume of the playback device based on one or more of the second loudness levels.

    METHODS AND APPARATUS TO FINGERPRINT AN AUDIO SIGNAL VIA EXPONENTIAL NORMALIZATION

    公开(公告)号:WO2021108186A1

    公开(公告)日:2021-06-03

    申请号:PCT/US2020/061077

    申请日:2020-11-18

    Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to fingerprint an audio signal via exponential normalization. An example apparatus includes an audio segmenter to divide an audio signal into a plurality of audio segments including a first audio segment and a second audio segment, the first audio segment including a first time-frequency bin, the second audio segment including a second time-frequency bin, a mean calculator to determine a first exponential mean value associated with the first time frequency bin based on a first magnitude of the audio signal associated with the first time frequency bin and a second exponential mean value associated with the second time frequency bin based on a second magnitude of the audio signal associated with the second time frequency bin and the first exponential mean value. The example apparatus further includes a bin normalizer to normalize the first time-frequency bin based on the second exponential mean value and a fingerprint generator to generate a fingerprint of the audio signal based on the normalized first time-frequency bins.

    DETECTION OF VOLUME ADJUSTMENTS DURING MEDIA REPLACEMENT EVENTS USING LOUDNESS LEVEL PROFILES

    公开(公告)号:WO2020102633A1

    公开(公告)日:2020-05-22

    申请号:PCT/US2019/061633

    申请日:2019-11-15

    Abstract: In one aspect, an example method includes (i) determining, by a playback device, a loudness level of first media content that the playback device is receiving from a first source; (ii) comparing, by the playback device, the determined loudness level of the first media content with a reference loudness level indicated by a loudness level profile for the first media content; (iii) determining, by the playback device, a target volume level for the playback device based on a difference between the determined loudness level of the first media content and the reference loudness level; and (iv) while the playback device presents second media content from a second source in place of the first media content, adjusting, by the playback device, a volume of the playback device toward the target volume level.

    TRANSITION DETECTOR NEURAL NETWORK
    6.
    发明申请

    公开(公告)号:WO2021207648A1

    公开(公告)日:2021-10-14

    申请号:PCT/US2021/026651

    申请日:2021-04-09

    Abstract: In one aspect, an example method includes (i) extracting a sequence of audio features from a portion of a sequence of media content; (ii) extracting a sequence of video features from the portion of the sequence of media content; (iii) providing the sequence of audio features and the sequence of video features as an input to a transition detector neural network that is configured to classify whether or not a given input includes a transition between different content segments; (iv) obtaining from the transition detector neural network classification data corresponding to the input; (v) determining that the classification data is indicative of a transition between different content segments; and (vi) based on determining that the classification data is indicative of a transition between different content segments, outputting transition data indicating that the portion of the sequence of media content includes a transition between different content segments.

    METHODS AND APPARATUS FOR AUDIO EQUALIZATION BASED ON VARIANT SELECTION

    公开(公告)号:WO2021108664A1

    公开(公告)日:2021-06-03

    申请号:PCT/US2020/062360

    申请日:2020-11-25

    Abstract: Methods, apparatus, systems and articles of manufacture are disclosed methods and apparatus for audio equalization based on variant selection. An example apparatus includes a processor to obtain training data, the training data including a plurality of reference audio signals each associated with a variant of music and organize the training data into a plurality of entries based on the plurality of reference audio signals, a training model executor to execute a neural network model using the training data, and a model trainer to train the neural network model by updating at least one weight corresponding to one of the entries in the training data when the neural network model does not satisfy a training threshold.

    METHODS AND APPARATUS TO FINGERPRINT AN AUDIO SIGNAL VIA NORMALIZATION

    公开(公告)号:WO2020051451A1

    公开(公告)日:2020-03-12

    申请号:PCT/US2019/049953

    申请日:2019-09-06

    Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to fingerprint audio via mean normalization. An example apparatus for audio fingerprinting includes a frequency range separator to transform an audio signal into a frequency domain, the transformed audio signal including a plurality of time-frequency bins including a first time-frequency bin, an audio characteristic determiner to determine a first characteristic of a first group of time-frequency bins of the plurality of time-frequency bins, the first group of time-frequency bins surrounding the first time-frequency bin and a signal normalizer to normalize the audio signal to thereby generate normalized energy values, the normalizing of the audio signal including normalizing the first time-frequency bin by the first characteristic. The example apparatus further includes a point selector to select one of the normalized energy values and a fingerprint generator to generate a fingerprint of the audio signal using the selected one of the normalized energy values.

    SYSTEMS, METHODS, AND APPARATUS TO IMPROVE MEDIA IDENTIFICATION

    公开(公告)号:WO2020051148A1

    公开(公告)日:2020-03-12

    申请号:PCT/US2019/049357

    申请日:2019-09-03

    Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to improve media identification. An example apparatus includes a hash handler to generate a first set of reference matches by performing hash functions on a subset of media data associated with media to generate hashed media data based on a first bucket size, a candidate determiner to identify a second set of reference matches that include ones of the first set, the second set including ones having first quantities of hits that did not satisfy a threshold, determine second quantities of hits for ones of the second set by matching ones to the hash tables based on a second bucket size, and identify one or more candidate matches based on at least one of (1) ones of the first set or (2) ones of the second set, and a report generator to generate a report including a media identification.

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