Abstract: Provided is a quick-responsive voice control technique even in use in a planetarium. A control device of a projector of a planetarium includes: a storage unit that stores a plurality of commands for controlling the projector, flags indicating whether or not the respective commands can be executed, and keywords associated with the respective commands; a voice acquisition unit that acquires voice data; a control unit that controls the control device; and a communication unit that communicates with the projector.

Abstract: An electronic apparatus including a memory configured to store first voice recognition information related to a first language and second voice recognition information related to a second language, and a processor to obtain a first text corresponding to a user voice that is received on the basis of first voice recognition information, based on an entity name being included in the user voice according to the obtained first text, identify a segment in the user voice in which the entity name is included. The processor is to obtain a second text corresponding to the identified segment of the user voice on the basis of the second voice recognition information, and obtain control information corresponding to the user voice on the basis of the first text and the second text.

Abstract: A method and an apparatus for calculating a downmixed signal and a residual signal are provided. According to the method, if a first target frame (a current frame or a previous frame of the current frame) is a switching frame, a to-be-encoded downmixed signal and a to-be-encoded residual signal of the subband corresponding to the preset frequency band in the current frame is calculated based on a switch fade-in/fade-out factor of a second target frame, an initial downmixed signal and an initial residual signal of the preset frequency band.

Abstract: Disclosed is an electronic apparatus which may receive a user voice of a user to be registered as a start command for activating a speech recognition function of the electronic apparatus; identify whether the user voice is misrecognized as a reference audio, wherein the reference audio includes a voice uttered by a user with high frequency from among a plurality of voices previously uttered by the user; and based on the user voice being not misrecognized as the reference audio, register the user voice as the start command.

Abstract: Methods and systems for a multimodal conversational system are described. A method for interactive multimodal conversation includes parsing multimodal conversation from a physical human for content, recognizing and sensing one or more multimodal content from the parsed content, identifying verbal and non-verbal behavior of the physical human from the one or more multimodal content, generating learned patterns from the identified verbal and non-verbal behavior of the physical human, training a multimodal dialog manager with and using the learned patterns to provide responses to end-user multimodal conversations and queries, and training a virtual human clone of the physical human with interactive verbal and non-verbal behaviors of the physical human, wherein appropriate interactive verbal and non-verbal behaviors are provided by the virtual human clone when providing the responses to the end-user multimodal conversations and queries.

Abstract: A computer-implemented method that includes receiving audio data corresponding to an utterance of a voice command captured by a user device. The user device has a plurality of different users. The method includes determining a particular user among the plurality of different users of the user device as a speaker of the utterance based on a comparison between the audio data and corresponding speaker verification data stored on memory hardware for each user of the plurality of different users of the user device. The method further includes, based on determining the particular user among the plurality of different users of the user device as the speaker of the utterance, providing, for output from the user device, a message comprising a speaker identifier associated with the particular user.

Abstract: Disclosed is an operating method of an electronic device, including receiving a first user model from another electronic device of a user registered in the electronic device, through a communication circuit of the electronic device, refining a user model of the electronic device based on the first user model, and identifying the user based on a first voice input of the user by using the refined user model, wherein the user model is trained by the electronic device based on a second user model of at least one another user other than the user before the user is registered, and wherein the first user model is trained by the another electronic device based on a second voice input of the user obtained by the another electronic device of the user.

Abstract: An electronic apparatus is provided. The electronic apparatus may include a microphone; a memory configured to store a wakeup word; and a processor configured to: identify, based on context information of the electronic apparatus, an occurrence of a pre-determined event; change, based on the occurrence of the pre-determined event, a first threshold value for recognizing the wakeup word; obtain, based on a first user voice input received via the microphone, a similarity value between first text information corresponding to the first user voice input and the wakeup word; and perform, based on the similarity value being greater than or equal to the first threshold value, a voice recognition function on second text information corresponding to a second user voice input received via the microphone after the first user voice input.

Abstract: A content reproduction apparatus includes an outputter configured to output audio and video, a user interface configured to receive an utterance input from a user, a memory storing one or more instructions, and a processor configured to execute the one or more instructions stored in the memory. The processor is configured to control the outputter to output a first screen in which one or more objects selectable by the user's utterance are included and a focus is displayed with respect to one of the one or more objects, and, to control the outputter to output utterable guide information for a next selection according to the object corresponding to the focus displayed, when the user does not provide an utterance through the user interface.

Abstract: Implementations of the subject technology provide systems and methods for multi-mode voice triggering for audio devices. An audio device may store multiple voice recognition models, each trained to detect a single corresponding trigger phrase. So that the audio device can detect a specific one of the multiple trigger phrases without consuming the processing and/or power resources to run a voice recognition model that can differentiate between different trigger phrases, the audio device pre-loads a selected one of the voice recognition models for an expected trigger phrase into a processor of the audio device. The audio device may select the one of the voice recognition models for the expected trigger phrase based on a type of a companion device that is communicatively coupled to the audio device.

Abstract: Described herein are systems and methods for utilizing ensemble learning methods to extract semantics of data in buildings by retrieving a plurality of data sets from a plurality of data sources associated with an automated environment; labeling a subset of the plurality of data sets by applying Natural Language Processing (NLP) on manufacturer specifications to generate a plurality of labels associated with the subset of the plurality of data sets, respectively; training a learning model on the subset of the plurality of data sets and the plurality of labels; and applying the learning model on remanding subset of the plurality of data sets to generate a semantic map indicative of semantic arrangement of the plurality of data sources associated with the automated environment.

Abstract: The disclosure provides an entity linking method and apparatus, and relates to the technical field of computers. The entity linking method comprises: recognizing a to-be-disambiguated entity in a target text; encoding the to-be-disambiguated entity to obtain a text code; encoding candidate entities corresponding to the to-be-disambiguated entity to obtain entity description codes; determining co-occurrence features between the target text and entity description information of the candidate entities; and determining an entity object corresponding to the to-be-disambiguated entity according to the text code, the entity description codes and the co-occurrence features.

Abstract: A display apparatus includes an input unit configured to receive a user command; an output unit configured to output a registration suitability determination result for the user command; and a processor configured to generate phonetic symbols for the user command, analyze the generated phonetic symbols to determine registration suitability for the user command, and control the output unit to output the registration suitability determination result for the user command. Therefore, the display apparatus may register a user command which is resistant to misrecognition and guarantees high recognition rate among user commands defined by a user.

Abstract: An electronic apparatus and a control method thereof are provided. The electronic apparatus includes a communication interface configured to receive content comprising image data and speech data; a memory configured to store a language contextual model trained with relevance between words; a display; and a processor configured to: extract an object and a character included in the image data, identify an object name of the object and the character, generate a bias keyword list comprising an image-related word that is associated with the image data, based on the identified object name and the identified character, convert the speech data to a text based on the bias keyword list and the language contextual model, and control the display to display the text that is converted from the speech data, as a caption.

Abstract: Embodiments herein relate to a method performed by a first network node (140) in a wireless communications network (100), for handling media channels during an ongoing media session. The ongoing media session is a session comprising a first UE (120), a second UE (121) and the first network node (140). The first network node (140) obtains, from the first UE (120), a voice instruction comprising a keyword for invoking a third party service within the media session. The first network node (140) further detects the keyword for invoking the third party service within the media session. The first network node (140) modifies, based on the detection of the keyword, a media channel between the first network node (140) and the second UE (121) to be silent. The first network node (140) further modifies, based on the detection of the keyword, a media channel between the first network node (140) and a third party network device (150) to be unsilent.

Abstract: A natural language processing system may select a synthesized speech quality using user profile data. The system may receive a natural language input and determine responsive output data. The system may, based at least in part on user profile data associated with the input, determine response configuration data corresponding to a quality of synthesized speech. The system may then determine further output data for presentation using the responsive output data and response configuration data.

Abstract: According to one embodiment, a method, computer system, and computer program product for solution guided generation of responses for dialog systems is provided. The embodiment may include receiving, by a processor, first voice data associated with a first user utterance in conversation in a guided dialog system. The embodiment may include identifying from the first voice data a first topic of a set of topics associated with the first user utterance. The embodiment may include identifying a first solution associated with the first topic. The first solution having one or more solution segments for accomplishing a task related to the topic. The embodiment may include generating a first response for a second user based on a first solution segment of the first solution and the first voice data.

Abstract: System and method for generating disambiguated terms in automatically generated transcripts and employing the system are disclosed. Exemplary implementations may: obtain a set of transcripts representing various speech from users; obtain indications of correlated correct and incorrect transcripts of spoken terms; use a vector generation model to generate vectors for individual instances of the correctly transcribed terms and individual instances the incorrectly transcribed terms based on text and contexts of the individual transcribed terms; and train the vector generation model to reduce spatial separation of the vectors generated for the spoken terms in the correlated correct transcripts and the incorrect transcripts.

Abstract: This document relates to machine learning. One example includes a method or technique that can be performed on a computing device. The method or technique can include obtaining a task-semantically-conditioned generative model that has been pretrained based at least on a first training data set having unlabeled training examples and semantically conditioned based at least on a second training data set having dialog act-labeled utterances. The method or technique can also include inputting dialog acts into the semantically-conditioned generative model and obtaining synthetic utterances that are output by the semantically-conditioned generative model. The method or technique can also include outputting the synthetic utterances.

Abstract: Methods, systems, and apparatuses for improved speech recognition and transcription of user utterances are described herein. A user utterance may be processed by a speech recognition computing device. One or more acoustic features associated with the user utterance may be used to determine whether one or more actions are to be performed based on a transcription of the user utterance.