Abstract: A server supports multiple virtual assistants. It receives requests that include wake phrase audio and an identification of the source of the request, such as a virtual assistant device. Based on the identification, the server searches a database for a wake phrase detector appropriate for the identified source. The server then applies the wake phrase detector to the received wake phrase audio. If the wake phrase audio triggers the wake phrase detector, the server provides an appropriate response to the source.

Abstract: A server supports multiple virtual assistants. It receives requests that include wake phrase audio and an identification of the source of the request, such as a virtual assistant device. Based on the identification, the server searches a database for a wake phrase detector appropriate for the identified source. The server then applies the wake phrase detector to the received wake phrase audio. If the wake phrase audio triggers the wake phrase detector, the server provides an appropriate response to the source.

Abstract: A server supports multiple virtual assistants. It receives requests that include wake phrase audio and an identification of the source of the request, such as a virtual assistant device. Based on the identification, the server searches a database for a wake phrase detector appropriate for the identified source. The server then applies the wake phrase detector to the received wake phrase audio. If the wake phrase audio triggers the wake phrase detector, the server provides an appropriate response to the source.

Abstract: There is provided a computing system for training a model for spotting of a custom wake phrase, the system comprising a processor and a memory in communication with the processor, the memory storing instructions that, when executed by the processor, configure the computing system to: receive a request for training the model for a phrase spotter executable for spotting the custom wake phrase within audio input. The computing system is configured to: responsive to receiving the request, receive, at a user interface of the computing system: an input positive audio sample corresponding to spoken audio of the custom wake phrase; and train using the input positive audio sample, the model for the phrase spotter executable for a wake phrase recognition subsystem that, when deployed on a voice enabled computing device, recognizes subsequent audio input instances of the custom wake phrase based upon the training.