Abstract: Implementations described herein relate to configuring a dynamic warm word button, that is associated with a client device, with particular assistant commands based on detected occurrences of warm word activation events at the client device. In response to detecting an occurrence of a given warm word activation event at the client device, implementations can determine whether user verification is required for a user that actuated the warm word button. Further, in response to determining that the user verification is required for the user that actuated the warm word button, the user verification can be performed. Moreover, in response to determining that the user that actuated the warm word button has been verified, implementations can cause an automated assistant to perform the particular assistant command associated with the warm word activation event. Audio-based and/or non-audio-based techniques can be utilized to perform the user verification.

Abstract: Implementations described herein relate to configuring a dynamic warm word button, that is associated with a client device, with particular assistant commands based on detected occurrences of warm word activation events at the client device. In response to detecting an occurrence of a given warm word activation event at the client device, implementations can determine whether user verification is required for a user that actuated the warm word button. Further, in response to determining that the user verification is required for the user that actuated the warm word button, the user verification can be performed. Moreover, in response to determining that the user that actuated the warm word button has been verified, implementations can cause an automated assistant to perform the particular assistant command associated with the warm word activation event. Audio-based and/or non-audio-based techniques can be utilized to perform the user verification.

Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.

Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.

Abstract: Various implementations include determining whether further spoken input is intended to correct at least one word in a candidate text representation of spoken input. Various implementations include receiving audio data capturing spoken input of a user. Various implementations include rendering output based on the candidate text representation to the user. Various implementations include receiving, while the output is being rendered, further audio data capturing the further spoken input. In response to determining the further spoken input is intended to correct the at least one word in the candidate text representation, various implementations include generating a revised text representation of the spoken input by altering at least one word in the candidate text representation based on one or more terms in the further candidate text representation.

Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.

Abstract: Implementations described herein relate to configuring a dynamic warm word button, that is associated with a client device, with particular assistant commands based on detected occurrences of warm word activation events at the client device. In response to detecting an occurrence of a given warm word activation event at the client device, implementations can determine whether user verification is required for a user that actuated the warm word button. Further, in response to determining that the user verification is required for the user that actuated the warm word button, the user verification can be performed. Moreover, in response to determining that the user that actuated the warm word button has been verified, implementations can cause an automated assistant to perform the particular assistant command associated with the warm word activation event. Audio-based and/or non-audio-based techniques can be utilized to perform the user verification.

Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.

Abstract: Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.