Abstract:
A system and method are provided for processing sound signals. The processing may include identifying individual harmonic sounds represented in sound signals, determining sound parameters of harmonic sounds, classifying harmonic sounds according to source, and/or other processing. The processing may include transforming the sound signals (or portions thereof) into a space which expresses a transform coefficient as a function of frequency and chirp rate. This may facilitate leveraging of the fact that the individual harmonics of a single harmonic sound may have a common pitch velocity (which is related to the chirp rate) across all of its harmonics in order to distinguish an the harmonic sound from other sounds (harmonic and/or non-harmonic) and/or noise.
Abstract:
A system and method may be provided to segment and/or classify an audio signal from transformed audio information. Transformed audio information representing a sound may be obtained. The transformed audio information may specify magnitude of a coefficient related to energy amplitude as a function of frequency for the audio signal and time. Features associated with the audio signal may be obtained from the transformed audio information. Individual ones of the features may be associated with a feature score relative to a predetermined speaker model. An aggregate score may be obtained based on the feature scores according to a weighting scheme. The weighting scheme may be associated with a noise and/or SNR estimation. The aggregate score may be used for segmentation to identify portions of the audio signal containing speech of one or more different speakers. For classification, the aggregate score may be used to determine a likely speaker model to identify a source of the sound in the audio signal.
Abstract:
Disclosed are systems, apparatuses, and methods for implementing a phase- model neural network using a fixed amount of memory. Such a phase-model neural network includes a plurality of neurons, wherein each neuron is associated with two parameters — an activity and a phase. Example methods include (i) generating a sequence of variables associated with a probability distribution of phases and (ii) sequentially sampling the probability distribution of phases using a fixed amount of memory, regardless of a number of phases used in the phase-model neural network.
Abstract:
Systems and methods may be provided to execute a plurality of computation tasks across a plurality of computing resources of a computing system. In one aspect, a computer implemented method may execute a software application comprising a plurality of tasks on a computing system. The method may comprise loading the software application into the computing system, assigning the plurality of tasks to a plurality of computing resources of the computing system according to a first assignment, executing the plurality of tasks on the plurality of computing resources according to the first assignment. Each processing resource may be configured to generate and collect system activity monitoring (SAM) data. The method may further comprise collecting the SAM data from the plurality of processing resources, performing an analysis of the first assignment based on the collected SAM data and determining an adjustment to the first assignment based on the analysis.
Abstract:
A system and method may be configured to process an audio signal. The system and method may track pitch, chirp rate, and/or harmonic envelope across the audio signal, may reconstruct sound represented in the audio signal, and/or may segment or classify the audio signal. A transform may be performed on the audio signal to place the audio signal in a frequency chirp domain that enhances the sound parameter tracking, reconstruction, and/or classification.
Abstract:
A system and method may be configured to analyze audio information derived from an audio signal. The system and method may track sound pitch across the audio signal. The tracking of pitch across the audio signal may take into account change in pitch by determining at individual time sample windows in the signal duration an estimated pitch and an estimated fractional chirp rate of the harmonics at the estimated pitch. The estimated pitch and the estimated fractional chirp rate may then be implemented to determine an estimated pitch for another time sample window in the signal duration with an enhanced accuracy and/or precision.
Abstract:
Systems and methods to process packets of information using an on-chip processing system include a memory bank, an interconnect module, a controller, and one or more processing engines. The packets of information include a packet header and a packet payload. The packet header includes one or more operator codes. The transfer of individual packets is guided to a processing engine through the interconnect module and through the controller by operator codes included in the packets.
Abstract:
A system and method may be configured to reconstruct an audio signal from transformed audio information. The audio signal may be resynthesized based on individual harmonics and corresponding pitches determined from the transformed audio information. Noise may be subtracted from the transformed audio information by interpolating across peak points and across trough points of harmonic pitch paths through the transformed audio information, and subtracting values associated with the trough point interpolations from values associated with the peak point interpolations. Noise between harmonics of the sound may be suppressed in the transformed audio information by centering functions at individual harmonics in the transformed audio information, the functions serving to suppress noise between the harmonics.
Abstract:
Systems and methods to route packets of information within an integrated circuit, across one or more boards, racks, blades, and/or chassis, and/or across a connected network of packet processing engines include various modes of operation. Packets are routed to their destination, for example an individual packet processing engine. The packets of information include address-mode indicators, one or more destination port indicators, and/or (long-distance) addresses.
Abstract:
A system and method may be configured to analyze audio information. The system and method may include determining for an audio signal, an estimated pitch of a sound represented in the audio signal, an estimated chirp rate (or fractional chirp rate) of a sound represented in the audio signal, and/or other parameters of sound(s) represented in the audio signal. The one or more parameters may be determined through analysis of transformed audio information derived from the audio signal {e.g., through Fourier Transform, Fast Fourier Transform, Short Time Fourier Transform, Spectral Motion Transform, and/or other transforms). Statistical analysis may be implemented to determine metrics related to the likelihood that a sound represented in the audio signal has a pitch and/or chirp rate (or fractional chirp rate). Such metrics may be implemented to determine an estimated pitch and/or fractional chirp rate.