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.

Aspects relate to apparatuses and methods for generating queries and transcribing video resumes. An exemplary apparatus includes at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive, from a posting generator, a plurality of posting inputs from a plurality of postings, receive a video resume from a user, generate a plurality of queries as a function of the video resume based on a plurality of posting categories, transcribe, as a function of the plurality of queries, a plurality of user inputs from the video resume, wherein the plurality of user inputs is related to attributes of a user, and classify the plurality of user inputs to the plurality of posting inputs to match the user to the plurality of postings.

Aspects relate to apparatuses and methods for generating queries and transcribing video resumes. An exemplary apparatus includes at least a processor and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive, from a posting generator, a plurality of posting inputs from a plurality of postings, receive a video resume from a user, generate a plurality of queries as a function of the video resume based on a plurality of posting categories, transcribe, as a function of the plurality of queries, a plurality of user inputs from the video resume, wherein the plurality of user inputs is related to attributes of a user, and classify the plurality of user inputs to the plurality of posting inputs to match the user to the plurality of postings.

A system and method of learning and recognizing a user-defined keyword is provided. An acoustic signal is obtained comprising speech. An end-user is given ability to train keywords or wake words or their choice just by speaking to the device a few times generating prototype vectors to be associated with the keyword. These keywords can be in any language. At least one of a plurality of keywords or absence of any of the plurality of keywords is predicted utilizing prototype vectors generated from the training of the device.

A system and method of learning and recognizing a user-defined keyword is provided. An acoustic signal is obtained comprising speech. An end-user is given ability to train keywords or wake words or their choice just by speaking to the device a few times generating prototype vectors to be associated with the keyword. These keywords can be in any language. At least one of a plurality of keywords or absence of any of the plurality of keywords is predicted utilizing prototype vectors generated from the training of the device.

Present invention discloses an ADC and an analog-to-digital conversion method. The ADC includes: a clock generator, including M transmission gates, where the M transmission gates are configured to receive a first clock signal that is periodically sent and separately perform gating control on the first clock signal, so as to generate M second clock signals, M is an integer that is greater than or equal to 2; M ADC channels that are configured in a time interleaving manner, configured to receive one analog signal and separately perform, under the control of the M second clock signals, sampling and analog-to-digital conversion on the analog signal, so as to obtain M digital signals, where each ADC channel is corresponding to one clock signal of the M second clock signals; and an adder, configured to add the M digital signals together in a digital field, so as to obtain a digital output signal.

Present invention discloses an ADC and an analog-to-digital conversion method. The ADC includes: a clock generator, including M transmission gates, where the M transmission gates are configured to receive a first clock signal that is periodically sent and separately perform gating control on the first clock signal, so as to generate M second clock signals, M is an integer that is greater than or equal to 2; M ADC channels that are configured in a time interleaving manner, configured to receive one analog signal and separately perform, under the control of the M second clock signals, sampling and analog-to-digital conversion on the analog signal, so as to obtain M digital signals, where each ADC channel is corresponding to one clock signal of the M second clock signals; and an adder, configured to add the M digital signals together in a digital field, so as to obtain a digital output signal.

Various implementations disclosed herein include a training module configured to concurrently segment a plurality of vocalization instances of a voiced sound pattern (VSP) as vocalized by a particular speaker, who is identifiable by a corresponding set of vocal characteristics. Aspects of various implementations are used to determine a concurrent segmentation of multiple similar instances of a VSP using a modified hierarchical agglomerative clustering (HAC) process adapted to jointly and simultaneously segment multiple similar instances of the VSP. Information produced from multiple instances of a VSP vocalized by a particular speaker characterize how the particular speaker vocalizes the VSP and how those vocalizations may vary between instances. In turn, in some implementations, the information produced using the modified HAC process is sufficient to determine more a reliable detection (and/or matching) threshold metric(s) for detecting and matching the VSP as vocalized by the particular speaker.

Various implementations disclosed herein include a training module configured to concurrently segment a plurality of vocalization instances of a voiced sound pattern (VSP) as vocalized by a particular speaker, who is identifiable by a corresponding set of vocal characteristics. Aspects of various implementations are used to determine a concurrent segmentation of multiple similar instances of a VSP using a modified hierarchical agglomerative clustering (HAC) process adapted to jointly and simultaneously segment multiple similar instances of the VSP. Information produced from multiple instances of a VSP vocalized by a particular speaker characterize how the particular speaker vocalizes the VSP and how those vocalizations may vary between instances. In turn, in some implementations, the information produced using the modified HAC process is sufficient to determine more a reliable detection (and/or matching) threshold metric(s) for detecting and matching the VSP as vocalized by the particular speaker.

An apparatus for voice recognition transforms voice information into a phoneme sequence expressed by characters of individual phonemes corresponding to feature parameters of the voice information, determines, based on a first likelihood and a second likelihood, whether or not collation succeeds, executes a matching operation that includes associating, based on a collation result, individual phonemes of the phoneme sequence of the voice information at a time of a failure of collation and individual phonemes of a phoneme sequence of previous voice information with each other, and executes a determination operation that includes determining, based on a result of the association, whether or not the phoneme sequence of the voice information is based on repetitive vocalization.