Gracenote, Inc.

The Nielsen Comapny (US), LLC

The Nielson Company (US), LLC

Zafar Rafii

Markus Kurt Cremer

Robert Coover

Bongjun Kim

Todd J Hodges

Prem Seetharaman

Aneesh Vartakavi

Andreas Schmidt

Matthew James Wilkinson

Alexander Berrian

Joshua Ernest Morris

Joseph P Renner

Xiaochen Liu

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.

Methods and apparatus to fingerprint an audio signal via normalization

Methods, apparatus, systems and articles of manufacture are disclosed to improve detection of audio signatures. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to execute the instructions to: determine a first time difference of arrival for a first audio sensor of a meter and a second audio sensor of the meter based on a first audio recording from the first audio sensor and a second audio recording from the second audio sensor; determine a second time difference of arrival for the first audio sensor and a third audio sensor of the meter based on the first audio recording and a third audio recording from the third audio sensor; determine a match by comparing the first time difference of arrival to i) a first virtual source time difference of arrival and ii) a second virtual source time difference of arrival; in response to determining that the first time difference of arrival matches the first virtual source time difference of arrival, identify a first virtual source location as the location of a media presentation device presenting media; and remove the second audio recording to reduce a computational burden on the processor.

Methods and apparatus to improve detection of audio signatures

Methods and apparatus for harmonic source enhancement are disclosed herein. An example apparatus includes an interface to receive a media signal. The example apparatus also includes a harmonic source enhancer to determine a magnitude spectrogram of audio corresponding to the media signal; generate a time-frequency mask based on the magnitude spectrogram; and apply the time-frequency mask to the magnitude spectrogram to enhance a harmonic source of the media signal.

Methods and apparatus for harmonic source enhancement

Methods, apparatus and articles of manufacture to identify sources of network streaming services are disclosed. An example method includes receiving a first audio signal that represents a decompressed second audio signal, identifying, from the first audio signal, a parameter of an audio compression configuration used to form the decompressed second audio signal, and identifying a source of the decompressed second audio signal based on the identified audio compression configuration.

Methods, apparatus, and articles of manufacture to identify sources of network streaming services

Methods, apparatus, systems and articles of manufacture are disclosed to adjust device control information. The example apparatus comprises a light drive waveform generator to obtain metadata corresponding to media and generate device control information based on the metadata, the device control information to inform a lighting device to enable consecutive light pulses; an effect engine to apply an attack parameter and a decay parameter to consecutive light pulses corresponding to the device control information, the attack parameter and the decay parameter based on the metadata to affect a shape of the consecutive light pulses; and a color timeline generator to generate color information based on the metadata, the color information to inform the lighting device to change a color state.

Methods and apparatus to control light pulsing effects based on media content

Methods, apparatus and articles of manufacture to identify sources of network streaming services are disclosed. An example apparatus includes a coding format identifier to identify, from a received first audio signal representing a decompressed second audio signal, an audio compression configuration used to compress a third audio signal to form the second audio signal, and a source identifier to identify a source of the second audio signal based on the identified audio compression configuration.

Methods, apparatus and articles of manufacture to identify sources of network streaming services

Example systems and methods are audio identification based on data structure are disclosed. An example apparatus includes memory, and one or more processors to execute instructions to execute a constant Q transform on query time slices of query audio, binarize the constant Q transformed query time slices, execute a two-dimensional Fourier transform on query time windows within the binarized and constant Q transformed query time slices to generate two-dimensional Fourier transforms of the query time windows, sequentially order the two-dimensional Fourier transforms in a query data structure, and identify the query audio as a cover rendition of reference audio based on a comparison between the query data structure and a reference data structure associated with the reference audio.

Audio identification based on data structure

Example systems and methods for automated cover song identification are disclosed. An example apparatus includes at least one memory, machine-readable instructions, and one or more processors to execute the machine-readable instructions to at least execute a constant Q transform on time slices of first audio data to output constant Q transformed time slices, binarize the constant Q transformed time slices to output binarized and constant Q transformed time slices, execute a two-dimensional Fourier transform on time windows within the binarized and constant Q transformed time slices to output two-dimensional Fourier transforms of the time windows, generate a reference data structure based on a sequential order of the two-dimensional Fourier transforms, store the reference data structure in a database, and identify a query data structure associated with query audio data as a cover rendition of the audio data based on a comparison of the query and reference data structures.

Automated cover song identification

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 audio content.

Audio content recognition method and system

A cover song identification method implemented by a computing system comprises receiving, by a computing system and from a user device, harmonic pitch class profile (HPCP) information that specifies one or more HPCP features associated with target audio content. A major chord profile feature and a minor chord profile feature associated with the target audio content are derived from the HPCP features. Machine learning logic of the computing system determines, based on the major chord profile feature and the minor chord profile feature, a relatedness between the target audio content and each of a plurality of audio content items specified in records of a database. Each audio content item is associated with cover song information. Cover song information associated with an audio content item having a highest relatedness to the target audio content is communicated to the user device.

Cover song identification method and system

Methods and apparatus to extract a pitch-independent timbre attribute from a media signal are disclosed. An example apparatus includes an audio characteristic extractor to determine a logarithmic spectrum of an audio signal; transform the logarithmic spectrum of the audio signal into a frequency domain to generate a transform output; determine a magnitude of the transform output; and determine a timbre attribute of the audio signal based on an inverse transform of the magnitude.

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Berkeley, CA, United States of America

Zafar Rafii