A matching machine accordingly accesses a query fingerprint that includes query sub-fingerprints that have been generated from query segments of a portion of query audio. After selecting reference sub-fingerprints for comparison to the query sub-fingerprints, the matching machine identifies a best-matching subset of the reference sub-fingerprints by evaluating total matches between the query sub-fingerprints and different subsets of the reference sub-fingerprints. The match machine then generates a count vector that stores the total counts mapped to respective offsets from a reference point in the reference sub-fingerprints. The matching machine determines a maximum count among the total counts and classifies the reference sub-fingerprints as a match with the query sub-fingerprints based on the maximum count.

An audio fingerprinting system and method. A server receives an audio fingerprint of a first audio piece, searches a database for the audio fingerprint, retrieves an audio profile vector associated with the audio fingerprint, updates user preference information based on the audio profile vector, and selects a second audio piece based on the user preference information. The audio fingerprint is generated by creating a matrix based on the frequency measurements of the audio piece, and performing a singular value decomposition of the matrix. To expedite the search of the database and to increase matching accuracy, a subset of candidates in the database is identified based on the most prominent musical notes of the audio piece, and the search is limited to the identified subset. One of the attributes of the audio profile vector is a particular audio class. An identifier for the audio class is generated based on an average of audio fingerprints of the audio pieces belonging to the audio class.

Audio fingerprinting includes obtaining audio samples of a piece of audio, generating frequency representations of the audio samples, identifying increasing and decreasing energy regions in frequency bands of the frequency representations, and generating hashes of features of the piece of audio. Each hash of features corresponds to portions of the identified energy regions appearing in a respective time window. Each feature is defined as a numeric value that encodes information representing: a frequency band of an energy region appearing in the respective time window, whether the energy region appearing in the respective time window is an increasing energy region or whether the energy region appearing in the respective time window is a decreasing energy region, and a placement of the energy region appearing in the respective time window.

A method, system and a computer program product for determining Quality of Experience (QoE) in mobile communication networks, in particular for use with VoIP telephony, wherein a first audio fingerprint generated from a digital audio signal is received at a recipient, and a second audio fingerprint is generated from the digital audio signal at the receiver end. A comparison between the two audio fingerprints is used to determine a QoE metric. In a separate embodiment, a third audio fingerprint is generated at the recipient in response to audio captured by a microphone at the recipient of the digital audio signal, and the third audio fingerprint is compared to one of the first and second audio fingerprints to determine the QoE metric value.

The invention relates to a method, a device, a client-server system as well as a computer program product and computer program element for handling digital silence when fingerprinting digital media signals. A fingerprint comprising a number of sub-fingerprints for at least a part of the digital media signal is generated, (step 42), and the influence of at least one piece of the media signal on the fingerprint is removed or changed, (step 48), which piece corresponds to digital silence. The invention in a reliable way avoids a wrong identification of media signals, such as audio signals, where digital silence is included. The invention is also easy to implement by only requiring some of the functionalities already provided in a computer.

A device and/or method for allowing authorization of computing device association using human-perceptible signals includes forming an association between a computing device and a further computing device. The computing device computes a fingerprint of a common key derived during the forming of the association and emits a first audio stimuli based upon the computed fingerprint. The first audio stimuli is at least one octave number apart from a second audio stimuli of the further computing device emitted by the further computing device based upon the common key.

Methods and system for identifying multimedia content streaming through a television includes retrieving an audio signal from a multimedia content selected for rendering at the television. The retrieved audio signal is partitioned into a plurality of segments of small intervals. A particular segment is analyzed to identify acoustic modulation and to generate a distinct vector for the particular segment based on the acoustic modulation, wherein the vector defines a unique fingerprint of the particular segment of the audio signal. A content database on a server is queried using the vector of the particular segment to obtain content information for multimedia content that matches the fingerprint of the particular segment. The content information is used to identify the multimedia content and the source of the multimedia content that matches the audio signal received for rendering.

A method to generate audio fingerprints. It is characterised in that it comprises: a) centring a mask in a spectral peak of a plurality of spectral peaks of a spectrogram of an audio signal; b) defining spectral regions around said spectral peak by means of said mask; c) capturing average energies of each of said spectral regions; d) comparing each of said average energies between them; e) obtaining a bit for each comparison, each obtained bit indicating the result of each comparison; f) grouping each bit obtained by means of said comparison in order to constitute an audio fingerprint; and g) encoding of the encoded spectral peaks using coarse frequency bands in order to allow for fast comparison of fingerprints

A computer-implemented method for clustering audio fingerprints from different set top boxes into groups based on their similarities is disclosed. The computer server receives audio fingerprints generated at different set top boxes and partitions them into multiple groups such that audio fingerprints within a group correspond to a respective TV program being played at the respective set top boxes. Upon receipt of an audio fingerprint from a set top box, the computer server identifies a group of audio fingerprints that are substantially similar to the audio fingerprint, determines TV program information for the audio fingerprint in accordance with the channel metadata associated with the identified group of audio fingerprints, and returns the TV program information to the requesting set top box.