Abstract: A device to perform target sound detection includes a memory including a buffer configured to store audio data. The device includes one or more processors coupled to the memory. The one or more processors are configured to receive the audio data from the buffer. The one or more processors are configured to detect the presence or absence of one or more target non-speech sounds in the audio data. The one or more processors are further configured to generate a user interface signal, to indicate one of the one or more target non-speech sounds has been detected, and provide the user interface signal to an output device.

Abstract: A device to perform target sound detection includes one or more processors. The one or more processors include a buffer configured to store audio data and a target sound detector. The target sound detector includes a first stage and a second stage. The first stage includes a binary target sound classifier configured to process the audio data. The first stage is configured to activate the second stage in response to detection of a target sound. The second stage is configured to receive the audio data from the buffer in response to the detection of the target sound.

Abstract: A device to process speech includes a speech processing network that includes an input configured to receive audio data. The speech processing network also includes one or more network layers configured to process the audio data to generate a network output. The speech processing network includes an output configured to be coupled to multiple speech application modules to enable the network output to be provided as a common input to each of the multiple speech application modules.

Abstract: Various embodiments include methods and devices for compression and decompression of weight data sets. Some embodiments may include compressing weight data by receiving a weight data set of binary numbers representing weight values, generating a frame payload including a compressed first frame of a first subset of the weight values in the weight data set, and generating a block of compressed weight data having the frame payload. Some embodiments may include decompressing weight data by retrieving a block of compressed weight data, in which the block of compressed weight data includes a frame header associated with a frame payload, in which the frame header includes a normalization factor indicator, and in which the frame payload includes compressed weight values, and generating a first decompressed frame comprising decompressed weight values of the compressed weight values of the frame payload.

Abstract: A device to process speech includes a speech processing network that includes an input configured to receive audio data corresponding to audio captured by one or more microphones. The speech processing network also includes one or more network layers configured to process the audio data to generate a network output. The speech processing network includes an output configured to be coupled to multiple speech application modules to enable the network output to be provided as a common input to each of the multiple speech application modules. A first speech application module corresponds to a speaker verifier, and a second speech application module corresponds to a speech recognition network.

Abstract: Certain aspects of the present disclosure provide a method for processing input data by a set of configurable nonlinear activation function circuits, including generating an exponent output by processing input data using one or more first configurable nonlinear activation function circuits configured to perform an exponential function, summing the exponent output of the one or more first configurable nonlinear activation function circuits, and generating an approximated log softmax output by processing the summed exponent output using a second configurable nonlinear activation function circuit configured to perform a natural logarithm function.

Abstract: The energy consumed by data transfer in a computing device may be reduced by transferring data that has been encoded in a manner that reduces the number of one “1” data values, the number of signal level transitions, or both. A data destination component of the computing device may receive data encoded in such a manner from a data source component of the computing device over a data communication interconnect, such as an off-chip interconnect. The data may be encoded using minimum Hamming weight encoding, which reduces the number of one “1” data values. The received data may be decoded using minimum Hamming weight decoding. For other computing devices, the data may be encoded using maximum Hamming weight encoding, which increases the number of one “1” data values while reducing the number of zero “0” values, if reducing the number of zero values reduces energy consumption.

Abstract: Certain aspects of the present disclosure provide a processor, comprising: a configurable nonlinear activation function circuit configured to: determine, based on a selected nonlinear activation function, a set of parameters for the nonlinear activation function; and generate output data based on application of the set of parameters for the nonlinear activation function, wherein: the configurable nonlinear activation function circuit comprises at least one nonlinear approximator comprising at least two successive linear approximators, and each linear approximator of the at least two successive linear approximators is configured to approximate a linear function using one or more function parameters of the set of parameters.

Abstract: Certain aspects of the present disclosure provide a method for processing input data by a configurable nonlinear activation function circuit, including determining a nonlinear activation function for application to input data; determining, based on the determined nonlinear activation function, a set of parameters for a configurable nonlinear activation function circuit; and processing input data with the configurable nonlinear activation function circuit based on the set of parameters to generate output data.

Abstract: The energy consumed by data transfer in a computing device may be reduced by transferring data that has been encoded in a manner that reduces the number of one “1” data values, the number of signal level transitions, or both. A data destination component of the computing device may receive data encoded in such a manner from a data source component of the computing device over a data communication interconnect, such as an off-chip interconnect. The data may be encoded using minimum Hamming weight encoding, which reduces the number of one “1” data values. The received data may be decoded using minimum Hamming weight decoding. For other computing devices, the data may be encoded using maximum Hamming weight encoding, which increases the number of one “1” data values while reducing the number of zero “0” values, if reducing the number of zero values reduces energy consumption.

Abstract: Various embodiments include methods and devices for compression and decompression of weight data sets. Some embodiments may include compressing weight data by receiving a weight data set of binary numbers representing weight values, generating a frame payload including a compressed first frame of a first subset of the weight values in the weight data set, and generating a block of compressed weight data having the frame payload. Some embodiments may include decompressing weight data by retrieving a block of compressed weight data, in which the block of compressed weight data includes a frame header associated with a frame payload, in which the frame header includes a normalization factor indicator, and in which the frame payload includes compressed weight values, and generating a first decompressed frame comprising decompressed weight values of the compressed weight values of the frame payload.

Abstract: A device to process speech includes a speech processing network that includes an input configured to receive audio data corresponding to audio captured by one or more microphones. The speech processing network also includes one or more network layers configured to process the audio data to generate a network output. The speech processing network includes an output configured to be coupled to multiple speech application modules to enable the network output to be provided as a common input to each of the multiple speech application modules. A first speech application module corresponds to a speaker verifier, and a second speech application module corresponds to a speech recognition network.

Abstract: A device to process speech includes a speech processing network that includes an input configured to receive audio data corresponding to audio captured by one or more microphones. The speech processing network also includes one or more network layers configured to process the audio data to generate an output representation of the audio data. The speech processing network includes an output configured to be coupled to multiple speech application modules to enable the output representation to be provided as a common input to each of the multiple speech application modules.

Abstract: Methods, systems, and devices for systems and techniques for processing keywords in audio data are described. In some devices configured with a virtual assistant, an audio processing component may support a command-first, keyword-second voice activation procedure. The audio processing component may receive audio data from a microphone and may compress a portion of the audio data and store the compressed audio data in a first buffer and may store a portion of the audio data that is uncompressed in a second buffer. The audio processing component may use the uncompressed audio data to detect the presence of a keyword and use the compressed audio data to identify a command associated with the keyword. Upon detection of the keyword, the audio processing component may decompress the compressed audio data and transmit the decompressed audio data and the uncompressed audio data to a main processor of the device.

Abstract: A device to process speech includes a speech processing network that includes an input configured to receive audio data corresponding to audio captured by one or more microphones. The speech processing network also includes one or more network layers configured to process the audio data to generate an output representation of the audio data. The speech processing network includes an output configured to be coupled to multiple speech application modules to enable the output representation to be provided as a common input to each of the multiple speech application modules.

Abstract: A device to perform target sound detection includes one or more processors. The one or more processors include a buffer configured to store audio data and a target sound detector. The target sound detector includes a first stage and a second stage. The first stage includes a binary target sound classifier configured to process the audio data. The first stage is configured to activate the second stage in response to detection of a target sound. The second stage is configured to receive the audio data from the buffer in response to the detection of the target sound.

Abstract: Methods, systems, and devices for systems and techniques for processing keywords in audio data are described. In some devices configured with a virtual assistant, an audio processing component may support a command-first, keyword-second voice activation procedure. The audio processing component may receive audio data from a microphone and may compress a portion of the audio data and store the compressed audio data in a first buffer and may store a portion of the audio data that is uncompressed in a second buffer. The audio processing component may use the uncompressed audio data to detect the presence of a keyword and use the compressed audio data to identify a command associated with the keyword. Upon detection of the keyword, the audio processing component may decompress the compressed audio data and transmit the decompressed audio data and the uncompressed audio data to a main processor of the device.

Abstract: A mobile device may include at least one processor configured to generate a first set and second set of processed audio signals for use in a surround sound system. The mobile device may also include at least one output port adapted to provide the first set of processed audio signals for use in the surround sound system to at least two speakers. The mobile device may also include an output port adapted to provide the second set of processed audio signals for use in the surround sound system to headphone speakers.

Abstract: A method for providing variable root note support in an audio player is described. A file with Musical Instrument Digital Interface (MIDI) data and a set of user defined instruments is received. A metric is determined using a user defined root note in the user defined instruments, a key number for a MIDI note in the MIDI data, and a player specific root note. The key number is adjusted based on the metric.

Abstract: Embodiments of methods, apparatuses, devices and systems associated with combining or mixing digital media streams are disclosed.