Abstract: Systems and methods are described herein for enabling, on a local device, a voice control system that limits the amount of data needed to be transmitted to a remote server. A data structure to support a local speech-to-text model is built at the local device from stored transcriptions of previous queries and known commands, and associates actions with each transcription. The transcription of the particular query is generated using the local speech-to- text model and is used to identify an associated action to perform.

Abstract: Systems and methods are described herein for enabling, on a local device, a voice control system that limits the amount of data needed to be transmitted to a remote server. A data structure is built at the local device to support a local speech-to-text model by receiving a query and transmitting, to a remote server over a communication network, a request for a speech-to-text transcription of the query. The transcription is received from the remote server and stored in the data structure at the local device in association with an audio clip of the query. Metadata describing the query is used to train the local speech-to-text model to recognize future instances of the query.

Abstract: The system trains a model to provide information used to provide a synthesized speech response to a voice input. The model takes as input prosodic information that may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example. The system receives a plurality of voice inputs, each associated with prosodic metric, as well as a plurality of responses, each also associated with prosodic metrics. The system trains the model based on the plurality of voice inputs, the plurality of responses, the prosodic metrics of the voice inputs, and the prosodic metrics of the responses such that the model outputs information used to generate the response. The model may also take as input user profile information, emotion metrics, and transition information to generate output. The output of the training model may be used by the system to provide synthesized speech responses having relevant prosodic character to received voice inputs.

Abstract: The system provides a synthesized speech response to a voice input, based on the prosodic character of the voice input. The system receives the voice input and calculates at least one prosodic metric of the voice input. The at least one prosodic metric can be associated with a word, phrase, grouping thereof, or the entire voice input. The system also determines a response to the voice input, which may include the sequence of words that form the response. The system generates the synthesized speech response, by determining prosodic characteristics based on the response, and on the prosodic character of the voice input. The system outputs the synthesized speech response, which includes a more natural, relevant, or both answer to the call of the voice input. The prosodic character of the voice input and/or response may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example.

Abstract: Systems and methods are described to receive a query from a user and provide a reply that is appropriate for an age group of the user. A query for a media asset is received, where such query comprises an inputted term, and the query is determined to be received from a user belonging to a first age group. A context of the inputted term within the query is identified, and in response to the determining, based on the identified context, that the inputted term of the query is inappropriate for the first age group, a replacement term for the inputted term that is related to the inputted term and is appropriate for the first age group in the context of the query is identified. The query is modified to replace the inputted term with the identified replacement term, and a reply to the modified query is generated for output.

Abstract: Systems and methods for handling a query comprising a media quote are provided. One example method includes receiving, at a computing device, an input comprising a query. A media quote is identified based on the query. A media asset is identified based on the identified media quote. An action is performed at the computing device, the action based on the identified media asset.

Abstract: Systems and methods are presented for adaptive biometric authentication. According to one example method, a failure of a first type of biometric authentication is detected. In response to detecting the failure of the first type of biometric authentication, an alternative type of authentication is completed. In response to completing the alternative type of authentication, a biometric characteristic of a biometric signature is selectively modified in a stored user profile for processing a subsequent attempt of the first type of biometric authentication.

Abstract: Systems and methods for adjusting a sound level during a conference call are disclosed herein. Conferencing application receives an audio input including a first sound and a second sound. A user selectable element is generated for each sound in an user interface, where a user selection setting a first user selectable element associated with the first sound at a user-specified level is received. The sound level for the first sound is adjusted based on the user selection and output at the user-specified level while the second sound is output at a default sound level.

Abstract: The present disclosure relates to systems and methods for resolving an unresolved plot or storyline of a series and resolving it. A user may not view all episodes in a series of episodes, particularly if the series runs over a long period of time, such as several years. The user may however be interested and curious to know how the series ends, with reference to a storyline that runs throughout the series. Therefore the disclosure provides methods and systems for determining if a user is interested in the resolution of an unresolved storyline and generating a resolution video for display.

Abstract: Insertion of supplemental content into a virtual environment is automated using a machine learning model. The machine learning model is trained to calculate a confidence value that a candidate virtual object fits into a virtual environment based on an input that includes a candidate virtual object, a list of persistent virtual objects, and a list of temporary virtual objects. The machine learning model is trained using the persistent and temporary objects displayed in the current virtual environment until it predicts that a selected virtual object fits into the current virtual environment. The trained machine learning model is then used to select a virtual object comprising supplemental content to be inserted as a new virtual object in the virtual environment.

Abstract: Systems and methods are disclosed herein for modifying modulated signals for transmission. The system receives a modulated signal comprising a speech signal and a carrier wave and generates first and second spectral signals by converting the modulation signal and carrier wave from the time domain to the frequency domain respectively. The system then determines spectral bands for the first and second spectral signals. For each spectral band, the system calculates a weighted spectral band value based on a magnitude of the first spectral signal within the spectral band and generates a modified spectral signal by modifying the second spectral signal with the weighted spectral band value. The system then converts the modified spectral signal from the frequency domain to the time domain and transmits the converted modified spectral signal to a server.

Abstract: Systems and methods for generating a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string including at least a content entity is received. A determination is made as to whether the text string includes an obsequious expression. In response to determining the text string includes an obsequious expression, a determination is made as to whether the obsequious expression describes the content entity. In response to determining whether the obsequious expression describes the content entity, the query is generated. In response to determining the obsequious expression describes the content entity, the content entity and the obsequious expression are included in the query and in response to determining the obsequious expression does not describe the content entity, the content entity is included in the query and the obsequious expression is excluded from the query.

Abstract: Systems and methods for training a natural language model of a natural language understanding (NLU) system are disclosed herein. A text string including at least a content entity is received. A determination is made as to whether the text string includes an obsequious expression. In response to determining the text string includes an obsequious expression, a determination is made as to whether the obsequious expression describes the content entity. A query is forwarded in response to determining the text string includes an obsequious expression and in determining the obsequious expression describes the content entity. In response to determining the obsequious expression describes the content entity, the query includes the obsequious expression and in response to determining the obsequious expression does not describe the content entity, the query does not include the obsequious expression.

Abstract: Systems and methods are provided for automatically responding to network connectivity issues in a media stream. One example method includes transmitting, from a first computing device, a media stream to one or more secondary computing devices. A network connectivity issue between the first computing device and one or more of the secondary computing devices is detected. If a network connectivity issue is detected, a notification is transmitted to one or more of the secondary computing devices.

Abstract: Systems and methods are presented herein for generating a new language understanding model, based on a user request. A user may input a root language and a locale into an application for generating a student language model. The application may generate the student language model and may identify a teacher language model related to the student language model. The application may compare data from the identified teacher language model to the student language model. The application may determine a subset of data from the teacher language model is not contained in the student language model. If the application determines at least a subset of data from the teacher language model is not in the student language model, the application may add at least the subset of data from the teacher language model to the student language model.

Abstract: Systems and methods for generating individualized content trailers. Content such as a video is divided into segments each representing a set of common features. With reference to a set of stored user preferences, certain segments are selected as aligning with the user's interests. Each selected segment may then be assigned a label corresponding to the plot portion or element to which it belongs. A coherent trailer may then be assembled from the selected segments, ordered according to their plot elements. This allows a user to see not only segments containing subject matter that aligns with their interests, but also a set of such segments arranged to give the user an idea of the plot, and a sense of drama, increasing the likelihood of engagement with the content.

Abstract: Methods and systems are disclosed herein for training a network to detect mimicked voice input, so that it can be determined whether a voice input signal is a mimicked voice signal. First voice data is received. The first voice data comprises at least a voice signal of a first individual and another voice signal. The voice signal of the first individual and at least one other voice signal is combined to create a composite voice signal. Second voice data is received. The second voice data comprises at least a voice signal of the first individual. The network is trained using at least the composite voice signal and the second voice data to determine whether a voice input signal is a mimicked voice input signal.

Abstract: Systems and methods are presented herein for providing a user with a notification, or access to content, based on the user's factual discourse during a conversation with other users. A first user may provide a first statement. A second user may provide a second statement. An application determines the first and the second statement are associated with first and second user profiles, respectively. The application analyzes the elements of each respective statement and determines there is a conflict between the user statements. In response to determining there is a conflict between the respective statements, the application generates a respective search query to verify each respective statement. When the application determines there is an answer that resolves the conflict between the respective statements, the application generates a notification for the users that comprises the answer that resolves the conflict and may include access to content affirming the answer.

Abstract: Systems and methods are described for extended reality environment interaction. An extended reality environment including an object is generated for display, and a first sensor is used to detect that a gaze has shifted from a first portion of the extended reality environment to a second portion of the extended reality environment, where the object is excluded from the first portion of the extended reality environment and included in the second portion of the extended reality environment. An indicator of the shift in the gaze is generated for display within the extended reality environment in response to detecting the gaze shift, and a voice command is detected by a second sensor while the indicator is in a vicinity of the object. In response to detecting the voice command, an action corresponding to the voice command may be executed.

Abstract: Systems and methods are described herein for interpreting natural language search queries that account for contextual relevance of words of the search query that would ordinarily not be processed, including, for example, processing each word of the query. Each term or phrase is associated with a respective part of speech, and a frequency of occurrence of a combination of adjacent terms or phrases public domain is determined. A relevance of each term is then determined based on its respective type of term and frequency of occurrence in the public domain. The natural language search query is then interpreted based on the importance or relevance of each term.