Abstract: A method for turn detection in a speech-to-speech model includes receiving, as input to the speech-to-speech (S2S) model, a sequence of acoustic frames corresponding to an utterance. The method further includes, at each of a plurality of output steps, generating, by an audio encoder of the S2S model, a higher order feature representation for a corresponding acoustic frame in the sequence of acoustic frames, and determining, by a turn detector of the S2S model, based on the higher order feature representation generated by the audio encoder at the corresponding output step, whether the utterance is at a breakpoint at the corresponding output step. When the turn detector determines that the utterance is at the breakpoint, the method includes synthesizing a sequence of output audio frames output by a speech decoder of the S2S model into a time-domain audio waveform of synthesized speech representing the utterance spoken by the user.

Abstract: Various arrangements for measuring blood pressure using sensor fusion are presented herein. Radio frequency (RF) signals are emitted and RF reflection signals are received by a radar sensor of a stationary device. The RF reflection signals are analyzed at a first distance range to identify a first pulse pressure waveform (PPW) at an aortic valve of a user. Vital sign data measured at an extremity of the user by a mobile device are received by the stationary device. The vital sign data is analyzed to identify a second PPW at the extremity of the user. Using the first PPW and the second PPW, a pulse transit time from the aortic valve to the extremity is determined. Using the PTT, a blood pressure (BP) of the user is determined and an indication of the BP is output.

Abstract: A method includes receiving one or more past trajectories navigated by a robotic device in an environment, wherein the one or more past trajectories are associated with initial environmental sensor data and one or more obstacle detection heuristics. The method also includes determining, based at least on subsequent environmental sensor data, one or more updated obstacle detection heuristics. The method further includes determining, based on the one or more updated obstacle detection heuristics and the initial environmental sensor data, one or more predicted drivable areas in the environment. The method additionally includes, based on the one or more predicted drivable areas including the one or more past trajectories, using the one or more updated obstacle detection heuristics to determine future navigation of the robotic device.

Abstract: A method includes receiving a text input including a sequence of words represented as an input encoder embedding. The input encoder embedding includes a plurality of tokens, with the plurality of tokens including a first set of grapheme tokens representing the text input as respective graphemes and a second set of phoneme tokens representing the text input as respective phonemes. The method also includes, for each respective phoneme token of the second set of phoneme tokens: identifying a respective word of the sequence of words corresponding to the respective phoneme token and determining a respective grapheme token representing the respective word of the sequence of words corresponding to the respective phoneme token. The method also includes generating an output encoder embedding based on a relationship between each respective phoneme token and the corresponding grapheme token determined to represent a same respective word as the respective phoneme token.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output temporal sequence of data elements conditioned on an input. In one aspect, a method comprises: obtaining the input, wherein the input comprises a noise input comprising a respective latent representation for each of a plurality of segments of the temporal sequence; updating, for each segment, the latent representation for the segment using a latent denoising neural network, the updating comprising, for each segment other than the first segment: obtaining a memory vector representing one or more hidden states generated by the latent denoising neural network when updating the latent representations for one or more preceding segments; updating the latent representation for the segment at each of a plurality of iterations; and generating the output temporal sequence of data elements by processing the latent representations for the plurality of segments.

Abstract: A system and method are disclosed. Audio input comprising the mixed audio signals is received by one or more client devices. The audio input is converted into a plurality of discrete tokens. A plurality of sound sources, each corresponding to a subset of discrete tokens of a plurality of subsets of discrete tokens, is determined using a trained machine learning model.

Abstract: A request of a user for a content item may be received, the user being associated with at least one of a set of preferences or a context. A group of similar users may be identified based the set of preferences or the context. A number of candidate content items corresponding to the content item may be identified. A difference in a measure of interaction of a first portion of the group after being provided the candidate content item and a second portion after not being provided the candidate content item may be determined for each candidate content item of the number of candidate content items. A subset may be determined based on the difference associated with each candidate content items. A candidate content item, identified based on at least one of the difference, an activity rate, or the context, may be provided to the user.

Abstract: Systems and methods are described that include operations such as detecting a plurality of computing devices configured as a distributed ambient computing system, receiving a request to execute a computing task, obtaining, from the distributed ambient computing system, data representing a device context for at least two of the plurality of devices, generating a combined context corresponding to the distributed ambient computing system, the combined context representing a combination of the device context for the at least two devices, generating and providing at least one decision request based on the computing task and the combined context, receiving a response to the at least one decision request, and triggering execution of the computing task based on the response and the combined context.

Abstract: This document discloses aspects of enforcing compliance of data use policies. In aspects, a network function receives, from an application, a message that includes data to upload from a device. In response, the network function executes a compliance function associated with a type of the data in the message. The compliance function can assert a data use policy based on a state (e.g., populated) of a field of the data and determine whether a user of the device has accepted the data use policy asserted for the data in the message. The compliance function can allow the upload of the data from the device based on compliance with the data use policy or blocks the upload of the data based on a lack of compliance with the data use policy. By so doing, the compliance function can ensure that data uploaded from the device complies with user-accepted data use policies.

Abstract: A method includes identifying, by a processing device, a third-party service provider of a plurality of third-party service providers that is authorized by a user to access data associated with the user. A data privacy score is generated based on one or more privacy risk factors. The data privacy score is associated with the third-party service provider. The data privacy score is indicative of a level of protection and privacy the third-party service provider maintains with respect to the data. A user interface (UI) displaying at least the data privacy score associated with the third-party service provider is provided for presentation on a client device associated with the user.

Abstract: Systems and methods for augmenting data can leverage one or more machine-learned models and contextual attention data to provide more realistic and efficient data augmentation. For example, systems and methods for inpainting can leverage a machine-learned model to generate predicted contextual attention data and blend the predicted contextual attention data with obtained contextual attention data to determine replacement data for augmenting an image to replace one or more occlusions. The obtained contextual attention data can include user-guided contextual attention.

Abstract: Some implementations relate to an automated assistant that can provide assistant suggestions based on content that the user has requested for the automated assistant to render at a computing device. In some instances, an assistant suggestion can correspond to a portion of the content that is not being rendered at the computing device but that is part of the content that the user is accessing. In other instances, an assistant suggestion can be based on data that can indicate how one or more users may have interacted with their automated assistant when viewing the content. Therefore, an assistant suggestion can correspond to an assistant operation that may have been initialized by another user who had previously viewed the content. In some implementations, an arrangement of the assistant suggestions can be modified according to which part of the content a user is viewing and/or user distance.

Abstract: The disclosed technology may comprise a mechanism that provides address range based memory hints, based on software memory access patterns. The mechanism includes an interface that can be in the form of a new instruction (“mem_range_hint”) that includes as operands (i) the start of the virtual address (“start_vaddr”), (ii) memory region size (“size”), and (iii) a hint (“hint”) associated with the memory access pattern.

Abstract: Systems and methods for providing a uni-card interface can provide for an interactive dynamic interface for providing information to a user. The uni-card interface may include a multi-state interface that can provide increasingly more detailed information upon each interaction. For example, the uni-card interface can provide a first state with condensed information, a second state with expanded information, and a third state with immersive information.

Abstract: A computer-implemented method for determining a score indicative of mindfulness of a user is provided. The method includes obtaining heart rate variability data of the user during a guided breathing exercise in which the user inhales and exhales to mimic a respiration rate associated with mindfulness. The method includes filtering the heart rate variability data to generate filtered heart rate variability. The method includes determining a first standard deviation of interbeat intervals indicative of respiratory sinus arrythmia and included in a first segment of the filtered heart rate variability data that spans a discrete interval of time. The method includes determining a second standard deviation of all interbeat intervals included in the first segment of the filtered heart rate variability data. The method includes determining a score indicative of mindfulness of the user based on the first standard deviation and the second standard deviation.

Abstract: A method includes identifying, by a processing device, a data structure including cells to store data, wherein the cells are arranged within rows and columns of the initial data structure. A scrambled data structure is created in which at least a subset of cells of the initial data structure is rearranged such that each cell of the rearranged subset of cells is located in at least one of a different row or a different column of the initial data structure. Responsive to receiving a user request to access the data of the initial data structure, the processing device determines whether to provide the user with access to the initial data structure or the scrambled data structure.

Abstract: A method includes receiving, by a processing device, a request to provide an entity with access to data associated with a user. A reference to location of the data within a data store controlled by the user and an access key associated with the data store is generated. Upon receiving an indication of user approval of the request, a response package is sent to the entity. The response package includes the reference to the location of the data, an obscured version of the data, and the access key. The data is obtained from the data store using the reference to the data and the access key provided by the entity. The data is provided to the entity.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for enabling artificial intelligence to generate new images based on contextual data and to generate digital components based on the images. In one aspect, a method includes receiving one or more queries from a client device of a user. A digital component is selected based on the one or more queries. A customized digital component is generated by obtaining an image of an object corresponding to the selected digital component and generating, using a language model, an image editing prompt for editing the image based on digital component data related to the digital component and query data including the one or more queries and contextual data. The image and the image editing prompt are provided to an image editing model. An edited image is received and used to generate the customized digital component.

Abstract: This document describes systems and techniques for indexing binaries of a software package and detecting potentially harmful code within the software package using API-call n-grams. A computing device generates API-call graphs from binaries. The computing device computes n-grams from the API-call graphs and adds them to an inverted index, which maps the n-grams to a respective identifier. The computing device identifies, using a signature that represents the behavior of the potentially harmful code, a set of candidate API-call graphs. The computing device can then compare, using a matching algorithm, the set of candidate API-call graphs to a non-deterministic finite automaton representation of the potentially harmful code. In this way, the described systems and techniques can use API-call n-grams to efficiently identify whether the software package includes a file that matches the behavior of potentially harmful code.

Abstract: A method includes receiving a prompt including a textual diarization request and corresponding audio data characterizing a conversation between multiple speakers. The method also includes generating a sequence of audio encoding chunks based on the corresponding data. For each respective audio encoding chunk, the method includes using a trained large language model (LLM) generating corresponding diarization results based on the respective audio encoding chunk and the textual diarization request and generating a new audio cohort for the respective audio encoding chunk based on the corresponding diarization results. The corresponding diarization results include a speech recognition result that has one or more predicted terms. Each respective predicted term is associated with a corresponding speaker token representing a predicted identity of a respective speaker that spoke the respective predicted term.