Google Inc.

Adrien Olczak

Nicolo D'Ercole

Alvin Abdagic

Mehek Sharma

Yang Lu

Akshay Kannan

Julia Proskurnia

Alessandro Agostini

Jennifer Daniel

Viesturs Zarins

Jackie Xiang

Dror Ayalon

Alexander Robertson

Ajay Gokhale

Jiawei Chen

Keqian Yan

Cristian Udrescu

Swante Scholz

Shumin Zhai

Nicolo D'ERCOLE

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

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Irvine, CA, United States of America

Adrien Olczak