Samsung Electronics Co., Ltd.

Hyungtak Choi

Inchul Hwang

Hyeonmok Ko

Jihie Kim

Haehun Yang

Seungsoo Kang

Seonghan Ryu

Daye Lee

Hongchul Kim

Hojung Lee

Jongyoub Ryu

Munjo Kim

Jongsun Lee

Hyunwoo Park

Eunji Lee

Sejin Kwak

Donghyeon Lee

Kwanho Lee

Yeseul Lee

Jisun Choi

Namkoo Lee

Sunghwan Baek

Jaechul Yang

Hannam Kim

Ikhee Shin

Heesik Jeon

Siddarth K M

Lohith Ravuru

Lohit Ravuru

Sunhwa Ko

Disclosed is an electronic device. The electronic device comprises: a microphone comprising circuitry; a speaker comprising circuitry; and a processor electrically connected to the microphone and speaker, wherein the processor, when a first user's voice is input through the microphone, identifies a user who uttered the first user's voice and provides a first response sound, which is obtained by inputting the first user's voice to an artificial intelligence model learned through an artificial intelligence algorithm, through the speaker, and when a second user's voice is input through the microphone, identifies a user who uttered the second user's voice, and if the user who uttered the first user's voice is the same as the user who uttered the second user's voice, provides a second response sound, which is obtained by inputting the second user's voice and utterance history information to the artificial intelligence model, through the speaker. In particular, at least some of the methods of providing a response sound to a user's voice may use an artificial intelligence model learned in accordance with at least one of a machine learning, neural network, or deep learning algorithm.

Electronic device and control method thereof

Provided are an electronic device for correcting a speech input, and an operating method thereof. The method may include receiving a first speech signal; obtaining first text; obtaining an intent of the first speech signal and a confidence score of the intent, by inputting the first text to a natural language understanding model; identifying a plurality of correction candidate semantic elements capable of being correction targets in the first text; receiving a second speech signal; obtaining second text; identifying whether the second speech signal is a speech signal for correcting the first text; comparing the plurality of correction candidate semantic elements in the first text with a semantic element in the second text, based on the confidence score; and correcting at least one of the plurality of correction candidate semantic elements in the first text.

Electronic device for correcting speech input of user and operating method thereof

A device for recognizing a speech input and an operating method thereof are provided. The device may be configured to: obtain one or more text candidates comprising a character string in which it is predicted that the speech input is to be converted by recognizing a speech input using an automatic speech recognition (ASR) model; extract text history information corresponding to the speech input from a database by comparing the speech input with a plurality of speech signals previously stored in the database; and perform training to adjust a weight of each of the one or more text candidates using the extracted text history information. Also, a method in which the device recognizes a speech input using an AI model may be performed.

Device for recognizing speech input of user and operating method thereof

An electronic device and a method for controlling thereof are provided. The electronic device includes a display, a memory storing at least one instruction, and a processor, wherein the processor is configured to, by executing the at least one instruction, extract a plurality of texts displayed on a chat window of a message application and collect the texts, input the plurality of collected texts into a trained first neural network model and align the plurality of texts in order, input the plurality of texts aligned in order into a trained second neural network model and identify whether additional information for acquiring event information from the plurality of texts is necessary, and acquire event information from the plurality of texts based on the identification result.

Acquiring event information from a plurality of texts

Provided in the present disclosure are an electronic device and a natural language generation method thereof. The natural language generation method of the electronic device comprises: obtaining input data with information on a plurality of slots included for generating a response; obtaining a natural language corresponding to the input data by inputting the information on the plurality of slots to one of artificial intelligence models trained for obtaining a natural language generation template and a natural language; and outputting the obtained natural language. In particular, at least a part of a method for obtaining a natural language in order to provide a response can use an artificial intelligence model having learned according at least one of machine learning, a neural network, or a deep-learning algorithm

Electronic device and natural language generation method thereof

An electronic apparatus and a controlling method thereof are provided. The method of controlling an electronic apparatus according to an embodiment includes: obtaining first text information including a plurality of words, identifying a security level of the first text information based on at least one of a source from which the first text information is obtained or a type of the first text information, obtaining second text information by converting at least one of the plurality of words included in the first text information based on the identified security level, and obtaining first summary sentence information summarizing the second text information through a summary module.

Electronic apparatus and controlling method thereof

An electronic device and a method for controlling the same are provided. The electronic device includes a microphone, a memory storing at least one instruction and dialogue history information, and a processor configured to be connected to the microphone and the memory and control the electronic device, in which the processor, by executing the at least one instruction, is configured to, based on a user's voice being input via the microphone, obtain response information for generating a response sentence to the user's voice, select at least one template phrase for generating the response sentence to the user's voice based on the stored dialogue history information, generate the response sentence using the response information and the at least one template phrase, and output the generated response sentence.

Electronic device and method for controlling the electronic device thereof

A server and a control method thereof are disclosed. The control method of a server includes receiving knowledge information from a first electronic device, storing the received knowledge information in a personal knowledge database corresponding to a user using the first electronic device, transmitting a response to an inquiry to obtain the knowledge information to at least one second electronic device based on the knowledge information stored in the personal knowledge database, based on the inquiry being received from the at least one second electronic device, receiving feedback information to the response from the at least one second electronic device, and storing the knowledge information in a global knowledge database based on the feedback information. At least a part of a method of allowing a server to provide a response to a user inquiry may use an artificial intelligence model learned according to at least one of machine learning, neural networks, or deep learning algorithms.

Server and control method thereof

Provided are a method and device for providing an event-emotion-based interactive interface by using an artificial intelligence (AI) system. The method includes identifying an emotional state of a user for at least one event by analyzing a response to a query, learning emotion information of the user for the at least one event, based on the emotional state of the user, determining an interaction type for the at least one event, based on the emotion information of the user, and providing notification information for the at least one event, based on the interaction type.

Method and system for providing an interactive interface

Growing community of inventors

Suwon-si, South Korea

Hyungtak Choi