Abstract: A method for detection of a keyword in a continuous stream of audio signal, by using a dilated convolutional neural network, implemented by one or more computers embedded on a device, the dilated convolutional network comprising a plurality of dilation layers, including an input layer and an output layer, each layer of the plurality of dilation layers comprising gated activation units, and skip-connections to the output layer, the dilated convolutional network being configured to generate an output detection signal when a predetermined keyword is present in the continuous stream of audio signal, the generation of the output detection signal being based on a sequence of successive measurements provided to the input layer, each successive measurement of the sequence being measured on a corresponding frame from a sequence of successive frames extracted from the continuous stream of audio signal, at a plurality of successive time steps.

Abstract: A method for detection of a keyword in a continuous stream of audio signal, by using a dilated convolutional neural network (DCNN), implemented by one or more computers embedded on a device, the dilated convolutional network (DCNN) comprising a plurality of dilation layers (DL), including an input layer (IL) and an output layer (OL), each layer of the plurality of dilation layers (DL) comprising gated activation units, and skip-connections to the output layer (OL), the dilated convolutional network (DCNN) being configured to generate an output detection signal when a predetermined keyword is present in the continuous stream of audio signal, the generation of the output detection signal being based on a sequence (SSM) of successive measurements (SM) provided to the input layer (IL), each successive measurement (SM) of the sequence (SSM) being measured on a corresponding frame from a sequence of successive frames extracted from the continuous stream of audio signal, at a plurality of successive time steps.

Abstract: A method for detection of a keyword in a continuous stream of audio signal, by using a dilated convolutional neural network (DCNN), implemented by one or more computers embedded on a device, the dilated convolutional network (DCNN) comprising a plurality of dilation layers (DL), including an input layer (IL) and an output layer (OL), each layer of the plurality of dilation layers (DL) comprising gated activation units, and skip-connections to the output layer (OL), the dilated convolutional network (DCNN) being configured to generate an output detection signal when a predetermined keyword is present in the continuous stream of audio signal, the generation of the output detection signal being based on a sequence (SSM) of successive measurements (SM) provided to the input layer (IL), each successive measurement (SM) of the sequence (SSM) being measured on a corresponding frame from a sequence of successive frames extracted from the continuous stream of audio signal, at a plurality of successive time steps.

Abstract: A method for detection of a keyword in a continuous stream of audio signal, by using a dilated convolutional neural network (DCNN), implemented by one or more computers embedded on a device, the dilated convolutional network (DCNN) comprising a plurality of dilation layers (DL), including an input layer (IL) and an output layer (OL), each layer of the plurality of dilation layers (DL) comprising gated activation units, and skip-connections to the output layer (OL), the dilated convolutional network (DCNN) being configured to generate an output detection signal when a predetermined keyword is present in the continuous stream of audio signal, the generation of the output detection signal being based on a sequence (SSM) of successive measurements (SM) provided to the input layer (IL), each successive measurement (SM) of the sequence (SSM) being measured on a corresponding frame from a sequence of successive frames extracted from the continuous stream of audio signal, at a plurality of successive time steps.

Abstract: As noted above, example techniques relate to local voice control. A device may monitoring an input sound-data stream representing sound detected by the one or more microphones for keywords and generate a first keyword detection event corresponding to a voice input when one or more keyword engines detect sound data matching at least one first keyword of the one or more keywords. The device determines whether the second voice input matches a particular predetermined speaker profile of one or more predetermined speaker profiles. Based on (i) generating the first keyword detection event and (ii) determining that the second voice input includes sound data matching the particular predetermined speaker profile, the device performs a particular playback command associated with the at least one first keyword.

Abstract: A method for detection of a keyword in a continuous stream of audio signal, by using a dilated convolutional neural network (DCNN), implemented by one or more computers embedded on a device, the dilated convolutional network (DCNN) comprising a plurality of dilation layers (DL), including an input layer (IL) and an output layer (OL), each layer of the plurality of dilation layers (DL) comprising gated activation units, and skip-connections to the output layer (OL), the dilated convolutional network (DCNN) being configured to generate an output detection signal when a predetermined keyword is present in the continuous stream of audio signal, the generation of the output detection signal being based on a sequence (SSM) of successive measurements (SM) provided to the input layer (IL), each successive measurement (SM) of the sequence (SSM) being measured on a corresponding frame from a sequence of successive frames extracted from the continuous stream of audio signal, at a plurality of successive time steps.