Abstract: An example process includes: receiving an audio stream; determining a plurality of acoustic representations of the audio stream, where each acoustic representation of the plurality of acoustic representations corresponds to a respective frame of the audio stream; obtaining a respective plurality of scores indicating whether each respective frame of the audio stream is directed to an electronic device, where the obtaining includes: determining, using a triggering model operating on the electronic device, for each acoustic representation, a score indicating whether the respective frame of the audio stream is directed to the electronic device; determining, based on the respective plurality of scores, a likelihood that the audio stream is directed to the electronic device; determining whether the likelihood is above or below a threshold; and in response to determining that the likelihood is below the threshold, ceasing to process the audio stream.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example method includes receiving, from one or more external electronic devices, a plurality of speaker profiles for a plurality of users; receiving a natural language speech input; determining, based on comparing the natural language speech input to the plurality of speaker profiles: a first likelihood that the natural language speech input corresponds to a first user of the plurality of users; and a second likelihood that the natural language speech input corresponds to a second user of the plurality of users; determining whether the first likelihood and the second likelihood are within a first threshold; and in accordance with determining that the first likelihood and the second likelihood are not within the first threshold: providing a response to the natural language speech input, the response being personalized for the first user.

Abstract: An example process includes: receiving an audio stream; determining a plurality of acoustic representations of the audio stream, where each acoustic representation of the plurality of acoustic representations corresponds to a respective frame of the audio stream; obtaining a respective plurality of scores indicating whether each respective frame of the audio stream is directed to an electronic device, where the obtaining includes: determining, using a triggering model operating on the electronic device, for each acoustic representation, a score indicating whether the respective frame of the audio stream is directed to the electronic device; determining, based on the respective plurality of scores, a likelihood that the audio stream is directed to the electronic device; determining whether the likelihood is above or below a threshold; and in response to determining that the likelihood is below the threshold, ceasing to process the audio stream.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example method includes receiving, from one or more external electronic devices, a plurality of speaker profiles for a plurality of users; receiving a natural language speech input; determining, based on comparing the natural language speech input to the plurality of speaker profiles: a first likelihood that the natural language speech input corresponds to a first user of the plurality of users; and a second likelihood that the natural language speech input corresponds to a second user of the plurality of users; determining whether the first likelihood and the second likelihood are within a first threshold; and in accordance with determining that the first likelihood and the second likelihood are not within the first threshold: providing a response to the natural language speech input, the response being personalized for the first user.

Abstract: An acoustic environment aware method for selecting a high quality audio stream during multi-stream speech recognition. A number of input audio streams are processed to determine if a voice trigger is detected, and if so a voice trigger score is calculated for each stream. An acoustic environment measurement is also calculated for each audio stream. The trigger score and acoustic environment measurement are combined for each audio stream, to select as a preferred audio stream the audio stream with the highest combined score. The preferred audio stream is output to an automatic speech recognizer. Other aspects are also described and claimed.