Abstract: Techniques are disclosed that enable automating user interface input by generating a sequence of actions to perform a task utilizing a multi-agent reinforcement learning framework. Various implementations process an intent associated with received user interface input using a holistic reinforcement policy network to select a software reinforcement learning policy network. The sequence of actions can be generated by processing the intent, as well as a sequence of software client state data, using the selected software reinforcement learning policy network. The sequence of actions are utilized to control the software client corresponding to the selected software reinforcement learning policy network.

Abstract: Interpretation of user commands is accelerated through digital user interfaces of various modalities, including generation and presentation of command modifications for rapid correction of incomplete or erroneous user commands. An embodiment detects whether the interpreted command is accurate and, if inaccurate, precisely what was the intended command or, at least, what suggested modification to the interpreted command would be sufficient to match the intent of the user. Disambiguation occurs that entails multiple recommendation generators proposing modified commands that may more accurately reflect the intent of the user. The user may provide a response that is either a confirmation of which one of several modified commands that were automatically proposed does the user intend or a correction that computer device may use to filter or replace currently offered modified commands to generate improved modified commands.

Abstract: Methods, systems, and related products that provide emotion-sensitive responses to user's commands and other utterances received at an utterance-based user interface. Acknowledgements of user's utterances are adapted to the user and/or the user device, and emotions detected in the user's utterance that have been mapped from one or more emotion features extracted from the utterance. In some examples, extraction of a user's changing emotion during a sequence of interactions is used to generate a response to a user's uttered command. In some examples, emotion processing and command processing of natural utterances are performed asynchronously.

Abstract: Provided are various mechanisms and processes for language acquisition using socio-neurocognitive techniques.

Abstract: The computer receives a group of conversation data associated with the escalation node, identifies agent responses in the conversation data, and clusters them into agent response types. The computer identifies dialog state feature value sets for the conversations. The computer identifies feature value set associations with response types, and generates, Boolean expressions representing the feature value sets associated with each of the response types. The computer makes a recommendation to add to at least one child node for the escalation node, with the child node corresponding to one of the response types. The child node has, as an entry condition, the Boolean expression for the response type to which the child node corresponds. The child node has as an action, which according to some aspects, provides a response representative of the cluster of agent responses for the response type to which the child node corresponds.

Abstract: A dialogue device enabling speech capable of improving a degree of intimacy with a user or a user satisfaction is provided. An input information acquiring unit (101) configured to acquire input information from a user, a focus information acquiring unit (103) configured to acquire focus information representing a focus in the input information, a user profile DB (110) configured to store profile information of the user and date and time information at which the profile information is registered in association with each other, a profile information acquiring unit (107) configured to acquire the profile information in accordance with a priority level determined on the basis of the date and time information from a user profile corresponding to the focus information stored in the user profile DB (110), and a speech generating unit (108) configured to generate a speech sentence (speech information) corresponding to the user profile are included.

Abstract: Sign language information processing method and apparatus, an electronic device and a readable storage medium provided by the present disclosure, achieve real-time collection of language data in a current communication of a user by obtaining voice information and video information collected by a user terminal in real time; and then match a speaking person with his or her speaking content by determining, in the video information, a speaking object corresponding to the voice information; and finally, make it possible for the user to clarify the corresponding speaking object when the user sees AR sign language animation in a sign language video by superimposing and displaying an augmented reality AR sign language animation corresponding to the voice information on a gesture area corresponding to the speaking object to obtain a sign language video. Therefore, it is possible to provide a higher user experience.

Abstract: A method includes receiving audio data corresponding to an utterance spoken by a user that includes a command for a digital assistant to perform a long-standing operation, activating a set of one or more warm words associated with a respective action for controlling the long-standing operation, and associating the activated set of one or more warm words with only the user. While the digital assistant is performing the long-standing operation, the method includes receiving additional audio data corresponding to an additional utterance, identifying one of the warm words from the activated set of warm words, and performing speaker verification on the additional audio data. The method further includes performing the respective action associated with the identified one of the warm words for controlling the long-standing operation when the additional utterance was spoken by the same user that is associated with the activated set of one or more warm words.

Abstract: A computer-implemented method of detecting a portion of audio data to be removed is provided. The method includes obtaining a recognition result of audio data. The recognition result includes recognized text data and time stamps. The method also includes extracting one or more candidate phrases from the recognition result using n-gram counts. The method further includes, for each candidate phrase, making pairs of same phrases with different time stamps and clustering the pairs of the same phrase by using differences in time stamps. The method includes further determining a portion of the audio data to be removed using results of the clustering.

Abstract: Aspects of the disclosure relate to systems and methods for increasing the speed, accuracy, and efficiency of language processing systems. A provided method may include storing a plurality of distinct rule sets in a database. Each of the rule sets may be associated with a different pipeline from a set of pipelines. The method may include receiving the utterance. The method may include tokenizing and/or annotating the utterance, determining a pipeline for the utterance, and comparing the utterance to the rule set that is associated with the pipeline. When a match is achieved between the utterance and the rule set, the method may include resolving the intent of the utterance based on the match. The method may include transmitting a request corresponding to the intent to a central server, receiving a response, and transmitting the response to the system user.

Abstract: Example embodiments provide techniques for configuring a natural-language processing system to perform a new function given at least one sample invocation of the function. The training data consisting of the sample invocation may be augmented by determining which subset of available training data most closely resembles the sample invocation and/or function. The effect of re-training a component this this augmented training data may be determined, and an annotator may review any annotations corresponding to the invocation if the effect is large.

Abstract: A user device configured to perform wake-up word detection in a target language.

Abstract: The present disclosure relates to methods, computer programs, and computer-readable media for processing a voice audio signal. A method includes receiving, at an electronic device, a voice audio signal, identifying spoken phrases within the voice audio signal based on the detection of voice activity or inactivity, dividing the voice audio signal into a plurality of segments based on the identified spoken phrases, and in accordance with a determination that a selected segment of the plurality of segments has a duration, Tseg, longer than a threshold duration, Tthresh, identifying a most likely location of a breath in the audio associated with the selected segment and dividing the selected segment into sub-segments based on the identified most likely location of a breath.

Abstract: Methods and systems are described herein for generating an audible presentation of a communication received from a remote server. A presentation of a media asset on a user equipment device is generated for a first user. A textual-based communication is received, at the user equipment device from the remote server. The textual-based communication is transmitted to the remote server by a second user and the remote server transmits the textual-based communication to the user equipment device responsive to determining that the second user is on a list of users associated with the first user. An engagement level of the first user with the user equipment device is determined. Responsive to determining that the engagement level does not exceed a threshold value, a presentation of the textual-based communication is generated in audible form.

Abstract: A server for supporting speech recognition of a device and an operation method of the server. The server and method identify a plurality of estimated character strings from the first character string and obtain a second character string, based on the plurality of estimated character strings, and transmit the second character string to the device. The first character string is output from a speech signal input to the device, via speech recognition.

Abstract: Disclosed are a method and a system for speech recognition, an electronic device and a storage medium, which relates to the technical field of speech recognition. Embodiments of the application comprise performing encoded representation on an audio to be recognized to obtain an acoustic encoded state vector sequence of the audio to be recognized; performing sparse encoding on the acoustic encoded state vector sequence of the audio to be recognized to obtain an acoustic encoded sparse vector; determining a text prediction vector of each label in a preset vocabulary; recognizing the audio to be recognized and determining a text content corresponding to the audio to be recognized according to the acoustic encoded sparse vector and the text prediction vector. The acoustic encoded sparse vector of the audio to be recognized is obtained by performing sparse encoding on the acoustic encoded state vector of the audio to be recognized.

Abstract: A voice recognition function link control system of a vehicle, which is configured for mounting a smart speaker used in the home or office in the vehicle and utilizing the smart speaker in linkage with an infotainment system of the vehicle, includes a traffic management system server, an infotainment system, a content service provider system server, and a smart speaker for receiving and transmitting a voice command of any user to the content service provider system server, receiving specific content from the content service provider system server, and outputting the received specific content.

Abstract: Disclosed is a method of providing a sign language video reflecting an appearance of a conversation partner. The method includes recognizing a speech language sentence from speech information, and recognizing an appearance image and a background image from video information. The method further comprises acquiring multiple pieces of word-joint information corresponding to the speech language sentence from joint information database, sequentially inputting the word-joint information to a deep learning neural network to generate sentence-joint information, generating a motion model on the basis of the sentence-joint information, and generating a sign language video in which the background image and the appearance image are synthesized with the motion model. The method provides a natural communication environment between a sign language user and a speech language user.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. An example process includes causing a first recognition result for a received natural language speech input to be displayed, where the first recognition result is in a first language and a second recognition result for the received natural language speech input is available for display responsive to receiving input indicative of user selection of the first recognition result, the second recognition result being in a second language. The example process further includes receiving the input indicative of user selection of the first recognition result and in response to receiving the input indicative of user selection of the first recognition result, causing the second recognition result to be displayed.

Abstract: A messaging system performs trend analysis on content produced by users of the messaging system. The messaging system is configured to extract modifications from content items received from client devices associated with users where the content items are modified using the modifications that comprises a text caption or a media overlay. The messaging system is further configured to determine one or more words from the content items and the extracted modifications and determine a frequency of the one or more words in the content items and the extracted modifications. The messaging system is further configured to determine whether the one or more words is a trend based on the frequency and an aggregate frequency. The messaging system is further configured to in response to the one or more words being determined as the trend, generating trend content associated with the one or more words, the trend content being a text, an image, or an augmentation content.