Google Inc.

Gray Ice Higdon

Alvin Abdagic

Nicolo D'Ercole

Zaheed Sabur

Megan Knight

Andrea Terwisscha Van Scheltinga

Bibo Xu

Jan Lamecki

Julia Proskurnia

Bo Zhang

Viesturs Zarins

Mehek Sharma

Adrien Olczak

Victor Carbune

Behshad Behzadi

Yang Lu

Luv Kothari

Akshay Kannan

Alessandro Agostini

Jacopo Sannazzaro Natta

Jennifer Daniel

Srikanth Pandiri

Krzysztof Andrzej Goj

Shumin Zhai

Swante Scholz

Cristian Udrescu

Keqian Yan

Jackie Xiang

Jiawei Chen

Ajay Gokhale

Alexander Robertson

Dror Ayalon

Implementations described herein relate to causing emoji(s) that are associated with a given emotion class expressed by a spoken utterance to be visually rendered for presentation to a user at a display of a client device of the user. Processor(s) of the client device may receive audio data that captures the spoken utterance, process the audio data to generate textual data that is predicted to correspond to the spoken utterance, and cause a transcription of the textual data to be visually rendered for presentation to the user via the display. Further, the processor(s) may determine, based on processing the textual data, whether the spoken utterance expresses a given emotion class. In response to determining that the spoken utterance expresses the given emotion class, the processor(s) may cause emoji(s) that are stored in association with the given emotion class to be visually rendered for presentation to the user via the display.

System(s) and method(s) for causing contextually relevant emoji(s) to be visually rendered for presentation to user(s) in smart dictation

Implementations described herein generally relate to generating a modification selectable element that may be provided for presentation to a user in a smart dictation session with an automated assistant. The modification selectable element may, when selected, cause a transcription, that includes textual data generated based on processing audio data that captures a spoken utterance and that is automatically arranged, to be modified. The transcription may be automatically arranged to include spacing, punctuation, capitalization, indentations, paragraph breaks, and/or other arrangement operations that are not specified by the user in providing the spoken utterance. Accordingly, a subsequent selection of the modification selectable element may cause these automatic arrangement operation(s), and/or the textual data locationally proximate to these automatic arrangement operation(s), to be modified. Implementations described herein also relate to generating the transcription and/or the modification selectable element on behalf of a third-party software application.

System(s) and method(s) to enable modification of an automatically arranged transcription in smart dictation

Determining whether, upon cessation of a second automated assistant session that interrupted and supplanted a prior first automated assistant session: (1) to automatically resume the prior first automated assistant session, or (2) to transition to an alternative automated assistant state in which the prior first session is not automatically resumed. Implementations further relate to selectively causing, based on the determining and upon cessation of the second automated assistant session, either the automatic resumption of the prior first automated assistant session that was interrupted, or the transition to the state in which the first session is not automatically resumed.

Determining whether to automatically resume first automated assistant session upon cessation of interrupting second session

Systems and methods described herein relate to determining whether to incorporate recognized text, that corresponds to a spoken utterance of a user of a client device, into a transcription displayed at the client device, or to cause an assistant command, that is associated with the transcription and that is based on the recognized text, to be performed by an automated assistant implemented by the client device. The spoken utterance is received during a dictation session between the user and the automated assistant. Implementations can process, using automatic speech recognition model(s), audio data that captures the spoken utterance to generate the recognized text. Further, implementations can determine whether to incorporate the recognized text into the transcription or cause the assistant command to be performed based on touch input being directed to the transcription, a state of the transcription, and/or audio-based characteristic(s) of the spoken utterance.

Voice commands for an automated assistant utilized in smart dictation

Growing community of inventors

Zurich, Switzerland

Alvin Abdagic