Abstract: Implementations are provided for providing responsive audio recordings to user queries that are prerecorded by human beings, rather than generated automatically using speech synthesis processing. In various implementations, a query provided by a user at an input component of a computing device may be used to search a corpus of voice recordings From the searching, a plurality of candidate responsive voice recordings may be identified and ranked based on measures of credibility associated with speakers that created the candidate responsive voice recordings. Based on the ranking, one or more of the plurality of candidate responsive voice recordings may be provided for presentation to the user at an output component of the same computing device or a different computing device.

Abstract: Methods and apparatus related to ranking modifications of a previous query. For example, modifications of a previous query may be generated based on a current query issued subsequent to the previous query by substituting one or more n-grams of the previous query with one or more n-grams of the current query. One or more measures of each of the modifications may be identified and, based on such measures, a ranking of each of the modifications may be determined. One of the modifications may be selected as a submission query based on the rankings of the modifications. The submission query may be selected for submission in lieu of, or in addition to, the current query.

Abstract: Location modeling may be generated for candidate locations based on validated location data. The location models for candidate locations may be based on validated location data associated with wireless access points that is validated using transaction data. Such validation may include comparing an identifier associated with candidate location data received from a client device to an identifier for a transaction account associated with a transaction from transaction data at a candidate location. Matching transaction data and candidate location data may generate validated location data to be used in generating location models for candidate locations.

Abstract: A method for example-driven machine learning is disclosed herein. The method comprises maintaining a plurality of dialog system rules and a knowledge database including a plurality of intent objects and a plurality of entity objects. The plurality of intent objects and the plurality of entity objects are associated with at least one dialog system rule. An exemplary phrase is received and one or more linguistic elements are retrieved from the exemplary phrase. It is determined that at least one of the linguistic elements is directed to at least one of the plurality of intent objects of the plurality of entity objects and the at least one of the linguistic elements in association with the at least one dialog system rule is added to the knowledge database.

Abstract: Example embodiments of the present disclosure provide for an example method. The example method includes generating an initial user interface including a content assistant component. The example method include obtaining user input data. The example method includes processing, by a machine learned model interfacing with the content assistant component, the data indicative of the input received from the user. The method includes obtaining output data, from the machine learned model interfacing with the content assistant component, indicative of one or more content item components. The method includes transmitting data which causes the content item components to be provided for display via an updated user interface. The method includes obtaining data indicative of user selection of approval of the content item components. The method includes generating, in response to obtaining the data indicative of the user selection of the approval of the content item components, content items.

Abstract: Techniques are described for selectively adapting and/or selectively utilizing a noise reduction technique in detection of one or more features of a stream of audio data frames. For example, various techniques are directed to selectively adapting and/or utilizing a noise reduction technique in detection of an invocation phrase in a stream of audio data frames, detection of voice characteristics in a stream of audio data frames (e.g., for speaker identification), etc. Utilization of described techniques can result in more robust and/or more accurate detections of features of a stream of audio data frames in various situations, such as in environments with strong background noise. In various implementations, described techniques are implemented in combination with an automated assistant, and feature(s) detected utilizing techniques described herein are utilized to adapt the functionality of the automated assistant.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for hotword detection on multiple devices are disclosed. In one aspect, a method includes the actions of receiving audio data that corresponds to an utterance. The actions further include determining that the utterance likely includes a particular, predefined hotword. The actions further include transmitting (i) data indicating that the computing device likely received the particular, predefined hotword, (ii) data identifying the computing device, and (iii) data identifying a group of nearby computing devices that includes the computing device. The actions further include receiving an instruction to commence speech recognition processing on the audio data. The actions further include in response to receiving the instruction to commence speech recognition processing on the audio data, processing at least a portion of the audio data using an automated speech recognizer on the computing device.

Abstract: Systems and methods for providing a program listing include storing user profile data and a user identifier for a user; storing an association of the user identifier with user identifiers for each of the plurality of social contacts of the user; receiving program identifier data representing programs currently being viewed by the social contacts; ranking the program identifier data for each of the plurality of social contacts based at least in part on the user profile data; and sending display data representing the program identifier data for display in an order based on the ranking.

Abstract: A content provider can provide content, such as advertisements or other promotional material, to a recipient. A distribution system of the content provider can receive a query and select one or more advertisements and a user interface for presenting the advertisements based on the query, information associated with the user, a set of queries received from the user, and/or other information. A model for selecting the user interface can be generated by serving available user interfaces randomly or pseudo-randomly and monitoring user interaction with the served user interfaces. The model can be updated during regular use based on the performance of the user interfaces.

Abstract: In some implementations, an utterance that requests a voice call is received, the utterance is classified as spoken by a particular known user, the particular known user is determined to be associated with a personal voice number, and in response to determining that the particular known user is associated with a personal voice number, the voice call is initiated with the personal voice number.

Abstract: Users of a communication system can initiate electronic payments during a communication session hosted by the communication system or via a social network identity page hosted by the communication system. The communication system detects a payment signal from a user of the communication system and the collects payment information details either by displaying a payment object interface in a communication application of the user or receiving payment information input directly from the user's communication device. The payment information includes sender and recipient payment account identifiers that are communicated to a payment processing system for processing and delivery of the designated payment amount to the recipient.

Abstract: Generating a prediction block for coding a block includes determining an adaptive intra-prediction mode indicative of at least a training region and a configuration of neighboring pixel locations. The training region neighbors the block and includes a plurality of reconstructed pixels. Filter coefficients are obtained. The filter coefficients are used to obtain respective prediction pixels of neighboring pixels within the training region when applied to defined respective configurations of the neighboring pixels according to the configuration of the neighboring pixels. The filter coefficients minimize a function of differences, each difference being a respective difference between a pixel in the training region and a prediction of that pixel in the training region.

Abstract: Mechanisms for managing output of an HDMI source are provided. In accordance with some implementations of the disclosed subject matter, a method for controlling output of an HDMI source is provided, the method comprising: establishing a connection between the HDMI source and an HDMI sink at a first address of a consumer electronic control bus of the HDMI sink; sending a request for an identity of the active source connected to the HDMI sink; monitoring signals on the consumer electronic control bus; receiving a message over the consumer electronic control bus identifying a second address on the consumer electronic control bus different from the first address as an address of an active source; setting a status of the HDMI source as inactive in response to receiving the message; and inhibiting output of video from the HDMI source to the HDMI sink in response to the status being set as inactive.

Abstract: Processor(s) of a client device can: identify a textual segment stored locally at the client device; process the textual segment, using a speech synthesis model stored locally at the client device, to generate synthesized speech audio data that includes synthesized speech of the identified textual segment; process the synthesized speech, using an on-device speech recognition model that is stored locally at the client device, to generate predicted output; and generate a gradient based on comparing the predicted output to ground truth output that corresponds to the textual segment. In some implementations, the generated gradient is used, by processor(s) of the client device, to update weights of the on-device speech recognition model. In some implementations, the generated gradient is additionally or alternatively transmitted to a remote system for use in remote updating of global weights of a global speech recognition model.

Abstract: A method includes receiving sampled audio data corresponding to utterances and training a machine learning (ML) model, using the sampled audio data, to generate a high-fidelity audio stream from a low bitrate input bitstream. The training of the ML model includes de-emphasizing the influence of low-probability distortion events in the sampled audio data on the trained ML model, where the de-emphasizing of the distortion events is achieved by the inclusion of a term in an objective function of the ML model, which term encourages low-variance predictive distributions of a next sample in the sampled audio data, based on previous samples of the audio data.

Abstract: For each audio pairing broadcast from an electronic device, reporting broadcasted pairing data including: broadcaster device group, broadcast data element, and broadcaster volume setting. For each reception, reporting received pairing data, including: receiver device group, received data element, and received signal score. Matching each received pairing data with zero or one instances of broadcasted pairing data based on a received data element matching the broadcast data element. For each broadcaster reporting a particular group and volume setting, identifying a received signal score value corresponding to a predetermined percentile of a density distribution of such scores matching broadcasters of the particular group. Determining, for each broadcaster of the group, a volume based on: the received signal score corresponding to the predetermined percentile and a reference received signal score.

Abstract: Described herein are systems and methods of converting media dimensions. A device may identify a set of frames from a video in a first orientation as belonging to a scene. The device may receive a selected coordinate on a frame of the set of frames for the scene. The device may identify a first region within the frame including a first feature corresponding to the selected coordinate and a second region within the frame including a second feature. The device may generate a first score for the first feature and a second score for the second feature. The first score may be greater than the second score based on the first feature corresponding to the selected coordinate. The device may crop the frame to include the first region and the second region within a predetermined display area comprising a subset of regions of the frame in a second orientation.