Google Inc.

Ramprasad Sedouram

Daniel Victor Klein

Apoorv Gupta

Shailly Kishtawal

Safia Ali

Merlyn Fraga Francis Xavier

Jaunani Sriramachandran

Manasi Rajan Kothari

Bhavinee Vyas

Puneetha Pai Brahmavar Pattanshet

A method includes processing, using a speech recognizer, a first portion of audio data to generate a first lattice, and generating a first partial transcription for an utterance based on the first lattice. The method includes processing, using the recognizer, a second portion of the data to generate, based on the first lattice, a second lattice representing a plurality of partial speech recognition hypotheses for the utterance and a plurality of corresponding speech recognition scores. For each particular partial speech recognition hypothesis, the method includes generating a corresponding re-ranked score based on the corresponding speech recognition score and whether the particular partial speech recognition hypothesis shares a prefix with the first partial transcription. The method includes generating a second partial transcription for the utterance by selecting the partial speech recognition hypothesis of the second plurality of partial speech recognition hypotheses having the highest corresponding re-ranked score.

Using personal attributes to uniquely identify individuals

Example aspects of embodiments of the present disclosure can provide for an example networked device for securely rendering distributed network resources, the networked device including one or more processors and one or more non-transitory, computer-readable media storing instructions executable to cause the one or more processors to perform operations. In some examples, the operations can include determining an occurrence of a system-level event on the networked device; responsive to determining the occurrence of the system-level event, executing, in a secure container, a request generation routine to generate a request for distributed content related to the system-level event; transmitting, using a network connection, the request; receiving, responsive to the request and using the network connection, a distributed content item; and rendering the distributed content item.

Content container integration with system events

Example embodiments of the present disclosure provide for an example method including obtaining data associated with a state of a user device. The example method includes obtaining data associated with navigational context associated with a user device. The example method includes obtaining content slot data indicative of a content slot for displaying a content item via a user device based on a state of the user device and an expected route. The example method includes selecting a content item for the content slot based on the navigational context. The example method includes transmitting data comprising instructions that when executed by the user device cause a content item to be displayed via the content slot.

Integration of content within navigation interface based on contextual data

Implementations relate to an automated assistant that can proactively detect and respond to a request for credentials. Characteristics of an entity requesting the credentials can be preemptively determined by the automated assistant using data that may be provided by the user or other previous visitors to a location. For example, the automated assistant can determine that the entity may expressly request certain information from a user when the user arrives at the location. Based on this determination, the automated assistant can operate to initialize an interface of a computing device of the user, when the user is determined to be at or near the location. For example, an audio interface of the computing device can be initialized to capture an audible request from a person who views credentials before granting access to a feature of the location.

Proactive rendering of credentials according to determined location characteristics

Embodiments according to examples aspects of the present disclosure provide for an example computer-implemented method. The example method can include obtaining a data structure configured for rendering a plurality of content containers on a user device, the plurality of content containers providing a collapsed configuration and an expanded configuration. The example method can include rendering, based on a first rate parameter descriptive of a user input associated with the user device, one or more of the plurality of content containers according to the collapsed configuration. The example method can include rendering, based on a second rate parameter, at least one of the plurality of content containers according to the expanded configuration.

Rate-adaptive content container

Implementations relate to an automated assistant that provides augmented reality content, via a display interface of computerized glasses, resulting from post-processing of application content. The application content can be identified based on prior interactions between a user and one or more applications, and the application content can be processed to determine objects, and/or object classifications, that may be associated with the application content. When the user is wearing the computerized glasses, and the object is detected within a field of view of the computerized glasses, the automated assistant can cause certain content to be rendered at the display interface of the computerized glasses. In some implementations, the content can be generated to supplement, and/or be different from, existing content that the user may have already accessed, in furtherance of preventing duplicative usage of applications and/or preserving computational resources.

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Bengaluru, India

Ramprasad Sedouram