An audio matching technique generates audio fingerprints from a captured audio signal. Coarse and Fine fingerprints are generated from the captured audio. The coarse fingerprint is used to match with a set of coarse fingerprints stored in a database to identify a subset of possibly matching database entries. The fine fingerprint is then used to perform a detailed comparison with fine fingerprints associated with the subset of possibly matching database entries in order to find a match for the captured audio signal.

Methods, systems and computer program products are provided for determining acoustic feature vectors of query and target items in a first vector space, and mapping the acoustic feature vectors to a second vector space having a lower dimension. The distribution of vectors in the second vector space can then be used to identify items from the same songs, and/or items that are complementary. A mapping function is trained using a machine learning algorithm, such that complementary audio items are closer in the second vector space than the first, according to a given distance metric.

A device may be configured to determine whether an audio file is a first type of audio file that is capable of being processed to recognize the voice query based on a characteristic of the audio file itself or a second type of audio file that may require speech recognition processing in order to recognize the voice query associated with the audio file. In determining whether the audio file is a first type of audio file or a second type of audio file, a query filter associated with the device may be configured to access one or more guidance queries. Using the one or more guidance queries, the device may classify the audio file as a first type of audio file or a second type of audio file based on receiving only a portion of the audio file, thereby improving the speed at which the audio file can be processed.

Disclosed are an electronic apparatus for dynamic note matching (DNM) and an operating method thereof, the method including acquiring a first section sequence by reducing a first sequence extracted from an input signal based on at least one first section in which the respective values are successively arranged; acquiring a second section sequence reduced from a pre-stored second sequence based on at least one second section in which the respective values are successively arranged; and calculating a similarity between the first section sequence and the second section sequence.

This disclosure relates generally to data processing devices and, more particularly, to a method, a device, and/or a system of structuring audio session data with independently queryable segments for efficient determination of high value content and/or generation of recombinant content. In one embodiment, a system for analyzing use of audio files to determine high value content includes a database server storing a data container referencing a segment data comprising an audio data and a segment UID that is independently addressable with a database query. A playback manager receives a playback request and streams the audio data to a device of a user. An interest marker engine receives an interest notification including a first audio time point and a second audio time point and generates an interest marker. An analytics server then generates an insight data from the interest marker and stores the insight data in association with the segment data.

This disclosure relates generally to data processing devices and, more particularly, to a method, a device, and/or a system of structuring audio session data with independently queryable segments for efficient determination of high value content and/or generation of recombinant content. In one embodiment, a system for analyzing use of audio files to determine high value content includes a database server storing a data container referencing a segment data comprising an audio data and a segment UID that is independently addressable with a database query. A playback manager receives a playback request and streams the audio data to a device of a user. An interest marker engine receives an interest notification including a first audio time point and a second audio time point and generates an interest marker. An analytics server then generates an insight data from the interest marker and stores the insight data in association with the segment data.

Methods, apparatus, systems and articles of manufacture are disclosed for scalable architectures for reference signature matching and updating. An example method for scalable architectures for reference signature matching and updating includes accessing site signatures to be compared to reference signatures from a first group of media sources. The example method also include determining if a first reference node is an owner of a first one of the site signatures, comparing a neighborhood of site signatures including the first site signature to reference signatures in a first subset of reference signatures when the first reference node is the owner of the first site signature, the first subset of references signatures stored in a first memory partition associated with the first reference node, and not comparing site signature to reference signatures when the first reference node is not the owner of the first one of the site signatures.

Implementations relate to determining a well-formed phrase to suggest to a user to submit in lieu of a not well-formed phrase. The suggestion is rendered via an interface that is provided to a client device of the user. Those implementations relate to determining that a phrase is not well-formed, identifying alternate phrases that are related to the not well-formed phrase, and scoring the alternate phrases to select one or more of the alternate phrases to render via the interface. Some of those implementations are related to identifying that the phrase is not well-formed based on occurrences of the phrase in documents that are generated by a source with the language of the phrase as the primary language of the creator.

A server is an interactive system that performs the interaction by performing a reverse question with respect to an input by the user and providing response content. An input acquisition unit and an answer generation unit constitute an interaction execution unit that repeatedly performs the interaction until a question sentence and an answer, which are the response content, satisfy a prescribed condition. Further, the stoppage determination execution unit performs control for stopping the interaction performed by the input acquisition unit and the answer generation unit based on the interaction state by the user or the other user. In a case where the interaction is stopped, the output unit provides the question sentence and the answer thereof at the time of stoppage to the communication terminal.

A server is an interactive system that performs the interaction by performing a reverse question with respect to an input by the user and providing response content. An input acquisition unit and an answer generation unit constitute an interaction execution unit that repeatedly performs the interaction until a question sentence and an answer, which are the response content, satisfy a prescribed condition. Further, the stoppage determination execution unit performs control for stopping the interaction performed by the input acquisition unit and the answer generation unit based on the interaction state by the user or the other user. In a case where the interaction is stopped, the output unit provides the question sentence and the answer thereof at the time of stoppage to the communication terminal.