Abstract: Systems and methods are presented for recognizing and responding to voice commands at a local system and selectively streaming audio to a network-based computing system to recognize voice commands when the user provides a specific voice command to stream to the network-based computing system and/or when the user provides a voice command that is not recognizable by the local system.

Abstract: A voice-activated system edge device cooperating with a remote command processor has a state machine defined by a listening mode state and a conversation monitoring mode state. The state machine transitions from the listening mode state to the conversation monitoring mode state in response to a wake word detection. A command accompanying the wake word is transmitted to the remote command processor for execution thereon. The conversation monitoring mode state is maintained for a conversation monitoring window time duration to receive a connection word accompanied by another command transmitted to the remote command processor for further execution thereon.

Abstract: Systems and methods presented herein generally include multi-wake phrase detection executed on a single device utilizing multiple voice assistants. Systems and methods presented herein can further include continuously running a Voice Activity Detection (VAD) process which detects presence of human speech. The multi-wake phrase detection can activate when the VAD process detects human speech. Once activated, the multi-wake phrase detection can determine which (if any) of the wake phrases of the multiple voice assistants might be in the detected speech. Operation of the multi-wake phrase detection can have a low miss-rate. In some examples, operation of the multi-wake phrase detection can be granular to accomplish the low miss-rates at low power with a tolerance for false positives on wake phrase detection.

Abstract: A system can include a circuit holistically customized for the detection of commands in an audio or video input signal to meet certain application-specific requirements. The circuit can have a neural network topology that is hardwired to perform detection based on application-specific detection criteria. The hardwired custom circuit can provide improved energy efficiencies compared to similar functionality carried out using software and generic hardware modules. The system can also include a sound change trigger module and perform non-voiced sound detection.