Abstract: In some cases, a verbal harassment detection system may use machine learning models to detect verbal harassment in real-time or near real-time. The system may receive an audio segment comprising a portion of audio captured by a microphone located within a vehicle. Further, the system may convert the audio segment to a text segment. The system may provide at least the text segment to a prediction model associated with verbal harassment detection to obtain a harassment prediction. Further, the system may provide the audio segment to an emotion detector to obtain a detected emotion of a speaking user that made an utterance included in the audio segment. Based at least in part on the harassment prediction and the detected emotion, the system may automatically, and without user intervention, determine whether a user is being harassed.

Abstract: The present document relates to audio coding systems which make use of a harmonic transposition method for high frequency reconstruction (HFR), and to digital effect processors, e.g. so-called exciters, where generation of harmonic distortion adds brightness to the processed signal. In particular, a system configured to generate a high frequency component of a signal from a low frequency component of the signal is described. The system may comprise an analysis filter bank (501) configured to provide a set of analysis subband signals from the low frequency component of the signal; wherein the set of analysis subband signals comprises at least two analysis subband signals; wherein the analysis filter bank (501) has a frequency resolution of ?f.

Abstract: Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for providing voice control using multiple digital assistants. In some embodiments, a voice platform operates to receive a voice input from a user. The voice platform selects a digital assistant from a plurality of digital assistants based on a trigger word. The voice platform then generates an intent from the voice input using the selected digital assistant. The voice platform then transmits the intent to a media device for processing.

Abstract: Systems and methods for dynamic sequence-based adjustment of prompt generation are provided. The system can receive a first interaction and a second interaction via a client device and identify a first sequence based on the first interaction and the second interaction. The system can map the first sequence to a node data structure and identify a node in the node data structure that matches the first sequence. The system can generate an adjusted parameter for a first digital component object responsive to a match with an attribute of the node in the node data structure. The system can execute a real-time digital component selection process among a plurality of digital component objects including the first digital component object to select the first digital component object. The system can transmit a prompt with the first digital component object to a client device to cause the client device to present the prompt.

Abstract: According to one embodiment of the present invention, a system for speech to media translation includes at least one processor. The at least one processor may be configured to receive an input in a first language and receive a command to translate the input. The input is one of text and audio. The at least one processor may be further configured to search an image database based on the input to retrieve contextually relevant images. The at least one processor may be configured to communicate the retrieved contextually relevant image to a target user.

Abstract: Machine classifiers in accordance with embodiments of the invention capture long-term temporal dependencies in the dialogue data better than the existing RNN-based architectures. Additionally, machine classifiers may model the joint distribution of the context and response as opposed to the conditional distribution of the response given the context as employed in sequence-to-sequence frameworks. Machine classifiers in accordance with embodiments further append random paddings before and/or after the input data to reduce the syntactic redundancy in the input data, thereby improving the performance of the machine classifiers for a variety of dialogue-related tasks. The random padding of the input data may further provide regularization during the training of the machine classifier and/or reduce exposure bias. In a variety of embodiments, the input data may be encoded based on subword tokenization.

Abstract: A vaporizer device may include a pressure sensor and an ambient pressure sensor. The pressure sensor may be configured to measure a first pressure in an air flow path in the vaporizer device. The ambient pressure sensor may be configured to measure a second pressure corresponding to an atmospheric pressure. The vaporizer device may further include a controller. The controller may be configured to transition the vaporizer device to a first standby mode when the first pressure is equal to or greater than the second pressure for a first threshold quantity of time. While the vaporizer device is in the first standby mode, the controller may be further configured to transition the vaporizer device to a second standby mode when the second pressure is a threshold quantity greater than the first pressure and no motion event is detected for a second threshold quantity of time.

Abstract: AM and LM parameters to be used for adapting an ASR model are derived for each audio segment of an audio stream comprising multiple audio programs. A set of identifiers, including a speaker identifier, a speaker domain identifier and a program domain identifier, is obtained for each audio segment. The set of identifiers are used to select most suitable AM and LM parameters for the particular audio segment. The embodiments enable provision of maximum constraints on the AMs and LMs and enable adaptation of the ASR model on the fly for audio streams of multiple audio programs, such as broadcast audio. This means that the embodiments enable selecting AM and LM parameters that are most suitable in terms of ASR performance for each audio segment.

Abstract: An integrated tele-health networking, interaction, and care-matching tool for tele-health services may include a tele-health operations server in communication with patient, provider, matching, and interaction databases. A management engine running on the server may execute a database management module, a rule module, and a GUI module configured to display a GUI having a plurality of preconfigured screens at a plurality of user terminals. In operation, the management engine implements a referral-based care network that connects a patient with healthcare providers, non-medical-professional caregivers, advocates, and friends or family via the user terminals.

Abstract: A method for improving speech signal intelligibility is performed at a device. A speech signal is obtained. A correspondence between the speech signal and a respective user group among different user groups having distinct voice characteristics is identified. Pre-encoding signal augmentation is performed on the speech signal with a respective pre-augmentation filtering coefficient that corresponds to the respective user group to obtain a group-specific pre-augmented speech signal. The device encodes the pre-augmented speech signal for subsequent transmission through the voice communication channel. An encoded version of the pre-augmented speech signal has reduced loss of signal quality as compared to an encoded version of the speech signal that is obtained without the pre-encoding signal augmentation.

Abstract: This disclosure describes a tabletop game assistant system configured to ingest and guide tangible games (such as board games, card games, etc.) using natural language interaction and image capture/visual display components. The system can include features enabling a game developer to “teach” the system the rules of a game using natural language, such as written instructions, to reduce or eliminate the need for writing dedicated code. The system may process images of a game board and/or tokens such as game pieces and/or cards to further generate game data in the form of a logical game model. The system can use the game data to guide human players of the game and, in some cases, participate as a player itself. The system may further be configured to observe a game and detect invalid actions, answer questions regarding the rules, and suggest moves. The system may provide additional utilities such as generating a random output (e.g., rolling virtual dice) and learning to recognize new game pieces.

Abstract: A performance analysis method according to the present invention includes generating information related to a performance tendency of a user, from observed performance information relating to a performance of a musical piece by the user and inferred performance information that occurs when the musical piece is performed based on a specific tendency.

Abstract: A method comprises receiving at least one natural language input, and determining an intent of the at least one natural language input. In the method, a virtual assistant of a plurality of virtual assistants is recommended to respond to the at least one natural language input based at least in part on the determined intent, and the at least one natural language input is transmitted to the recommended virtual assistant. The determining and recommending are performed using one or more machine learning models, and the plurality of virtual assistants respectively correspond to a plurality of different functions of an enterprise.

Abstract: An embodiment of the present invention generates natural language content from a set of keywords in accordance with a template. Keyword vectors representing a context for the keywords are generated. The keywords are associated with language tags, while the template includes a series of language tags indicating an arrangement for the generated natural language content. Template vectors are generated from the series of language tags of the template and represent a context for the template. Contributions from the contexts for the keywords and the template are determined based on a comparison of the series of language tags of the template with the associated language tags of the keywords. One or more words for each language tag of the template are generated to produce the natural language content based on combined contributions from the contexts for the keywords and the template.

Abstract: The current invention describes a method and system for delivering reconfigured digital content or reconfigured delivery of digital content designed to allay the effects of Q/D-related EMS. Disclosed is a system/method for delivering an extended digital therapeutic (ExRx) based on a selected emotional/mental state (EMS) and home-bound state (HBS).

Abstract: A computer-implemented method, system, and non-transitory computer-readable storage medium for enhancing performance of a first model. The first model is trained with a training data set. A second model receives the training data set associated with the first model. The second model provides the first model with a hardness value associated with prediction of each data point of the training data set. The first model determines a confidence value regarding predicting each data point based on the training data set, and determines a ratio of the hardness value of a prediction of each data point by the second model with respect to the confidence value of the first model. The first model is retrained with a re-weighted training data set when the determined ratio is lower than a value of ?.

Abstract: The present disclosure provides method and apparatus for providing personalized songs in automated chatting. A message may be received in a chat flow. Personalized lyrics of a user may be generated based at least on a personal language model of the user in response to the message. A personalized song may be generated based on the personalized lyrics. The personalized song may be provided in the chat flow.

Abstract: A speech-processing system configured to determine entities corresponding to ambiguous words such as anaphora (“he,” “she,” “they,” etc.) included in an utterance. The system may associate incoming utterances with a speaker identification (ID), device ID, and other data. The system then tracks entities referred to in utterances so that if a later utterance includes an ambiguous entity reference, the system may take the speaker ID, device ID, etc. from the ambiguous reference, along with the text of the utterance and other data, and compare that information to previously mentioned entities (or other entities that may be relevant) to identify the entity mentioned in the ambiguous statement. Once the entity is determined, the system may then complete command processing of the utterance using the identified entity.

Abstract: Disclosed is a system for delivering a digital therapeutic, specific to both a user-selected emotional or mental state (EMS) and at least one user profile attribute comprising of: an EMS store; a message prescriber; a processor coupled to a memory element with instructions, the processor when executing the memory-stored instructions, configure the system to cause: the EMS store comprising a plurality of EMS to allow a user to select at least one EMS, said selected EMS indicating at least one of an emotion, mental, and/or physical state of the user. The message prescriber then pushing to a user device at least one stored digital therapeutic coupled to the selected EMS from the EMS store, wherein the digital therapeutic is at least one of a message or content with a behavioral and/or physical (b/p) recommendation of varying severity and/or varying design cues specific to both the user-selected EMS and at least one user profile attribute.

Abstract: Provided in embodiments of the present application are a method and apparatus for user registration and electronic device. The method includes: after obtaining a wake-up voice of a user each time, extracting and storing a first voiceprint feature corresponding to the wake-up voice; clustering the stored first voiceprint features to divide the stored first voiceprint features into at least one category, wherein, each of the at least one category includes at least one first voiceprint feature which belongs to the same user; assigning one category identifier to each category; storing each category identifier in correspondence to at least one first voiceprint feature corresponding to this category identifier to complete user registration. The embodiments of the present application can simplify the user operation and improve the user experience.