Google Inc.

Sneha Ashok

Adam Coimbra

Cliff Kuang

Radu Voroneanu

Mugurel-Ionut Andreica

Dana Ritter

Diana Avram

Andre Elisseeff

Alice Liang

Huize Shi

Kyunghoon Lee

Deepak Goyal

Anton Berezin

Andreina Reyna

Implementations relate to determining a rendering type for an application that is executing automatically. Based on user interactions with an application that is associated with specified input from the user while the user is interacting with the application, a confidence metric is generated for each specified input and a rendering type is determined based on the confidence metrics. Subsequently, when the user requests that a sequence of actions be performed, the application will be displayed according to the rendering type.

Automatically executing application routines with user inputs

Methods, systems, devices, and tangible non-transitory computer readable media for generating assistive indications are provided. The disclosed technology can include accessing image data that includes at least one image. Character data can be generated based at least in part on the image data and one or more optical character recognition operations. Further, the character data can include one or more characters associated with the at least one image. One or more characters that are associated with one or more recognized words and the one or more characters that are associated with one or more unrecognized words can be determined based on the character data. One or more auditory indications including a synthetic voice reciting the one or more recognized words and the one or more unrecognized words can be generated. Furthermore, the synthetic voice can recite each of the one or more unrecognized words one character at a time.

Generating assistive indications based on detected characters

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San Jose, CA, United States of America

Sneha Ashok