Abstract: Implementations set forth herein relate to an automated assistant that can interact with applications that may not have been pre-configured for interfacing with the automated assistant. The automated assistant can identify content of an application interface of the application to determine synonymous terms that a user may speak when commanding the automated assistant to perform certain tasks. Speech processing operations employed by the automated assistant can be biased towards these synonymous terms when the user is accessing an application interface of the application. In some implementations, the synonymous terms can be identified in a responsive language of the automated assistant when the content of the application interface is being rendered in a different language. This can allow the automated assistant to operate as an interface between the user and certain applications that may not be rendering content in a native language of the user.

Abstract: Disclosed is an embedded chip package, comprising at least one chip and a frame surrounding the at least one chip, the chip having a terminal face and a back face separated by a height of the chip, the frame having a height equal to or larger than the height of the chip, wherein the gap between the chip and the frame is fully filled with a photosensitive polymer dielectric, the terminal face of the chip being coplanar with the frame, a first wiring layer being formed on the terminal face of the chip and a second wiring layer being formed on the back face of the chip. Moreover, a method for manufacturing an embedded chip package is disclosed.

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: Implementations set forth herein relate to an automated assistant that can interact with applications that may not have been pre-configured for interfacing with the automated assistant. The automated assistant can identify content of an application interface of the application to determine synonymous terms that a user may speak when commanding the automated assistant to perform certain tasks. Speech processing operations employed by the automated assistant can be biased towards these synonymous terms when the user is accessing an application interface of the application. In some implementations, the synonymous terms can be identified in a responsive language of the automated assistant when the content of the application interface is being rendered in a different language. This can allow the automated assistant to operate as an interface between the user and certain applications that may not be rendering content in a native language of the user.

Abstract: Generally, the present disclosure is directed to user interface understanding. More particularly, the present disclosure relates to training and utilization of machine-learned models for user interface prediction and/or generation. A machine-learned interface prediction model can be pre-trained using a variety of pre-training tasks for eventual downstream task training and utilization (e.g., interface prediction, interface generation, etc.).

Abstract: Methods and apparatus are described herein for selecting, from one or more electronic data sources, a candidate textual statement associated with an entity, identifying one or more attributes of the candidate textual statement; and determining, based on the identified one or more attributes of the candidate textual statement, a measure of suitability of the candidate textual statement for presentation as a testimonial about the entity.

Abstract: Methods and apparatus for determining a tone differential between a given segment of a document and a larger segment of the document. The tone differential may be based on comparison of a first tone associated with the given segment and a second tone associated with the larger segment. The tone differential is indicative of the variance between the tone of the given segment and the tone of the larger segment.

Abstract: Methods and apparatus are described herein for classifying user reviews or portions thereof as being related to various entities, and for associating extracted descriptive segments of text contained in those user reviews or portions thereof with entities based on the classifications. In various implementations, one or more categories of observed user interest may be identified based on a corpus of user queries. One or more segments of text related to the one or more categories of observed user interest may be detected in one or more user reviews associated with a product. Based on the detecting, the product may be indexed on the one or more categories of observed user interest in a searchable database. In some implementations, the searchable database may be accessible to one or more remote client devices, and may be searchable by the one or more categories of observed user interest to provide search results to be rendered by the one or more remote client devices.

Abstract: An envelope includes a first envelope panel, a second envelope panel, a padded layer, and a reinforcing arrangement. The first envelope panel has a main portion and a flap portion foldably extended from the main portion along a folding line. The second envelope panel has one second peripheral edge portion attached on a first peripheral edge portion of the main portion of the first envelope panel to form a receiving cavity and an access opening adjacent to the folding line. The reinforcing arrangement includes a reinforcing member attached on the first envelope panel along the folding line so as to provide structural reinforcement to the first envelope panel along the folding line.

Abstract: Methods and apparatus are described herein for classifying user reviews or portions thereof as being related to various entities, and for associating extracted descriptive segments of text contained in those user reviews or portions thereof with entities based on the classifications. In various implementations, one or more portions of a corpus of user reviews may be classified as being related to a first entity or a second entity. One or more descriptive segments of text may be extracted from the one or more classified portions. The one or more extracted descriptive segments of text may be associated with the first or second entity based on classifications of the one or more classified portions.

Abstract: Systems and methods are disclosed for determining media consumption preferences. A method may include accessing media consumption history associated with a user. The media consumption history may include at least one of media purchase history of the user, media viewing history of the user, and media listening history of the user. A media category preference of the user may be determined, based on the media consumption history. The media category preference may include a popularity indication for each of a plurality of media categories of media items in the media consumption history. Search results provided in response to a search query by the user and/or media recommendations prepared for the user may be scored based on the media category preference. The media may include a video, a movie, a TV show, a book, an audio recording, a music album and/or another type of digital media.

Abstract: A method employing a hybrid classification model is used to perform optical character recognition operations for an image. Image data from the image is provided to a generative classification model of the hybrid model, and generative image classifications operations are performed, generating a feature data set which is outputted from the generative classification model. This feature data set is then provided to the discriminative classification model, and discriminative classification operations are performed to generate a classification of the image.

Abstract: A document processing system and method thereof are disclosed. The system comprises machine-readable data such as DataGlyphs and human-readable data such as rendering text of the DataGlyphs that are applied on the document. Processing devices of the system can decode document-processing instruction(s) embedded in the machine-readable data, and then optionally execute at least part of the instruction automatically. A designed stamp is also provided to generate the machine-readable data and human-readable data on the document.

Abstract: Page turning of a three-dimensional electronic book is modeled as a dynamic animation. The page to be turned may be rotated by rotating it about a base line, and deformed by curling points of the front face of the turning page around the outer side of an imaginary geometric shape.

Abstract: A system and method for improving the appearance of a raster image that includes glyph shapes is provided. A pair of glyph shapes is defined. Each glyph shape is differentiated two-dimensional machine readable data of relatively uniform appearance. Each of the glyph shapes is assigned to a different bit value. Digital data from an input source is encoded into a bitmap image space by representing a bit value for each item of the digital data as the glyph shape corresponding to that bit value. A raster image of the encoded glyph shapes is generated from the bitmap image space.

Abstract: A method employing a hybrid classification model is used to perform optical character recognition operations for an image. Image data from the image is provided to a generative classification model of the hybrid model, and generative image classifications operations are performed, generating a feature data set which is outputted from the generative classification model. This feature data set is then provided to the discriminative classification model, and discriminative classification operations are performed to generate a classification of the image.

Abstract: A document processing system and method thereof are disclosed. The system comprises machine-readable data such as DataGlyphs and human-readable data such as rendering text of the DataGlyphs that are applied on the document. Processing devices of the system can decode document-processing instruction(s) embedded in the machine-readable data, and then optionally execute at least part of the instruction automatically. A designed stamp is also provided to generate the machine-readable data and human-readable data on the document.

Abstract: A system and method for improving the appearance of a raster image that includes glyph shapes is provided. A pair of glyph shapes is defined. Each glyph shape is differentiated two-dimensional machine readable data of relatively uniform appearance. Each of the glyph shapes is assigned to a different bit value. Digital data from an input source is encoded into a bitmap image space by representing a bit value for each item of the digital data as the glyph shape corresponding to that bit value. A raster image of the encoded glyph shapes is generated from the bitmap image space.

Abstract: A method for reducing the obtrusiveness of artifacts appearing in a glyph shape code image space includes encoding digital data values as a glyph shape code, such that the shape code is composed of glyphs having shapes that encode digital data values. Each distinct data value that is encoded is represented by the shape of a glyph, and these glyphs are spatially distributed in a bitmap image space. The bitmap image space is analyzed to determine the presence of artifacts within the bitmap image space, and a raster image is generated in which at least a single dot is placed within at least one of the artifacts in the image space.