Abstract: A helmet configured for improving the safety of a user of a personal mobility by measuring an electroencephalogram (EEG) of the user using an EEG detector provided in a helmet, determining an accident situation based on the measured EEG, and operating a safety device is provided. The helmet includes a body configured to form an exterior of the helmet and can be worn on a user's head; the EEG detector provided on the body and configured to detect EEG of the user; and a controller configured to determine an accident-related situation based on an EEG signal output from the EEG detector, and to generate a control signal for operating a safety device according to the determined accident-related situation.

Abstract: It is an aspect of the present disclosure to provide a dialogue system capable of providing an extended function to the user by registering a new vocabulary that matches the user's preference and by changing the pre-stored conversation pattern.

Abstract: A dialogue system includes a database, a voice recognition module configured to convert an utterance of a user in a vehicle into text, an intention determination module configured to identify intention of the user based on the text, an emotion determination module configured to identify the user's emotional state from the identified user's intention, and a controller configured to compare data indicating the identified intention of the user and the user's emotional state with rules stored in the database and determine whether to output a response to the user's utterance based on a result of the comparing.

Abstract: A dialogue system includes a Speech to Text (STT) engine configured to convert a user speech into a spoken text; a learning-based dialogue engine configured to determine a user intention corresponding to the spoken text; a storage configured to store learning data used for learning of the dialogue engine; and a controller configured to determine an actual user intention based on at least one of context information or an additional user speech, match a spoken text failing to determine the user intention with the actual user intention when the dialogue engine fails to determine the user intention corresponding to the spoken text, and the dialogue engine may perform learning using the spoken text stored in the storage and the actual user intention.

Abstract: A dialogue system includes a processor configured to: generate a meaning representation corresponding to an input sentence by performing Natural Language Understanding on the input sentence, generate an output sentence corresponding to the input meaning representation based on Recurrent Neural network (RNN), and determine whether the input sentence cannot be processed using the natural language generator. The processor calculates a parameter representing a probability of outputting the input sentence when the meaning representation corresponding to the input sentence is input to the natural language generator, and determines whether the input sentence cannot be processed based on the calculated parameter.

Abstract: It is an aspect of the present disclosure to provide a dialogue system capable of providing an extended function to the user by registering a new vocabulary that matches the user's preference and by changing the pre-stored conversation pattern.

Abstract: A dialogue processing apparatus includes: a speech input device configured to receive a speech signal of a user; a first buffer configured to store the received speech signal therein; an output device; and a controller. The controller is configured to: detect an utterance end time point on the basis of the stored speech signal; generate a second speech recognition result corresponding to a speech signal after the utterance end time point on the basis of whether an intention of the user is to be identified from a first speech recognition result corresponding to a speech signal before the utterance end time point; and control the output device to output a response corresponding to the intention of the user determined on the basis of at least one of the first speech recognition result or the second speech recognition result.

Abstract: A dialogue system includes: a storage configured to store a parameter tree including at least one parameter used for performing an action; a speech input device configured to receive speech from a user; an input processor configured to apply a natural language understanding algorithm to the received speech to generate a speech recognition result; a dialogue manager configured to determine an action corresponding to the received speech based on the speech recognition result, to retrieve a parameter tree corresponding to the action from the storage, and to determine additional information needed to perform the action based on the retrieved parameter tree; and a result processor configured to generate a dialogue response for requesting the additional information.

Abstract: It is an aspect of the present disclosure to provide a dialogue system capable of providing an extended function to the user by registering a new vocabulary that matches the user's preference and by changing the pre-stored conversation pattern.

Abstract: A vehicle includes a communication device configured to communicate with a user terminal. The vehicle further includes an input processor configured to recognize a voice of a telephone call received by the user terminal and generate a voice recognition result on the voice of the telephone call. The vehicle also includes a dialogue manager configured to determine telephone call contents based on the voice recognition result and determine whether or not to provide the telephone call contents to a user based on the telephone call contents.

Abstract: A dialogue system, a dialogue system control method, and an electronic apparatus are configured to process a user speech to generate a system response before the user's speech ends by recognizing the user's intention When the user's speech is finished, the system response is output to continue a natural dialogue flow in real time. The dialogue system includes: a Speech to Text engine to convert a user speech into text; an intermediate dialogue engine configured to process an intermediate speech before user speech is terminated; a final dialogue engine configured to process a final speech after the user speech is terminated; and a controller. The controller is configured to input the converted text to the intermediate dialogue engine when user speech is not terminated, and to input the converted text to the final dialogue engine when user speech is terminated The dialogue system also includes a Text to Speech engine configured to convert the system response into a speech signal.

Abstract: A hub-dialogue system includes a speech processor configured to determine a user intention that is included in inputted user dialogue. A communicator is configured to connect a local speaker corresponding to an external dialogue system through wireless communication. A controller is configured to determine the external dialogue system corresponding to the user intention from among a plurality of external dialogue systems, to generate a command sentence indicating the user intention, to convert the command sentence to a voice signal, and to control the communicator to transmit the voice signal to the local speaker corresponding to the determined external dialogue system.

Abstract: A natural language generating apparatus includes: a receiver configured to receive semantic expression information for generating a natural language sentence; and a controller configured to: generate a dependency tree representing a syntax structure of at least one word determined based on the received semantic expression information, based on a trained neural network model, and to generate the natural language sentence based on the generated dependency tree.

Abstract: A translating apparatus includes: a translator configured to translate an input sentence of a first language into a second language to generate a plurality of output sentences; a first dialogue manager configured to generate a meaning representation for the input sentence of the first language; a second dialogue manager configured to generate a meaning representation for each of the plurality of output sentences of the second language; and a determiner configured to determine a final output sentence among the plurality of output sentences of the second language based on the meaning representation for the input sentence of the first language and the meaning representation for each of the plurality of output sentences of the second language.

Abstract: A dialogue processing apparatus includes: a communicator configured to communicate with an external apparatus; a speech inputter configured to receive a speech of a user; and a controller configured, when the speech of the user is received, to determine whether it is possible to provide a function corresponding to the received speech, and to control the communicator to transmit speech information about the speech of the user to the external apparatus based on whether it is possible to provide the function corresponding to the received speech.

Abstract: A dialogue system includes: a speech recognizes configured to generate an input sentence by converting a speech of a user into a text; a dialogue manager configured to generate a meaning representation for the input sentence; and a result processor configured to generate a plurality of output sentences corresponding to the meaning representation. The dialogue manager generates a meaning representation for each of the plurality of output sentences. The result processor generates a system response based on the meaning representation for the input sentence and the meaning representation for each of the plurality of output sentences.

Abstract: A dialog processing system may include a communication device configured to receive information sent from the outside and circumstantial information; a storage configured to store a rule and a dialog template related the rule; a rule determiner configured to compare a condition of the rule and the information to generate a determined rule; a situation determiner configured to determine to express the determined rule based on the determined rule and circumstantial information collected from the outside; and a result processor configured to generate text to be expressed based on the determined rule and the dialog template and output the text according to a signal sent from the situation determiner.

Abstract: A helmet configured for improving the safety of a user of a personal mobility by measuring an electroencephalogram (EEG) of the user using an EEG detector provided in a helmet, determining an accident situation based on the measured EEG, and operating a safety device is provided. The helmet includes a body configured to form an exterior of the helmet and can be worn on a user's head; the EEG detector provided on the body and configured to detect EEG of the user; and a controller configured to determine an accident-related situation based on an EEG signal output from the EEG detector, and to generate a control signal for operating a safety device according to the determined accident-related situation.

Abstract: A dialogue system includes a Speech to Text (STT) engine configured to convert a user speech into a spoken text; a learning-based dialogue engine configured to determine a user intention corresponding to the spoken text; a storage configured to store learning data used for learning of the dialogue engine; and a controller configured to determine an actual user intention based on at least one of context information or an additional user speech, match a spoken text failing to determine the user intention with the actual user intention when the dialogue engine fails to determine the user intention corresponding to the spoken text, and the dialogue engine may perform learning using the spoken text stored in the storage and the actual user intention.

Abstract: A dialogue system includes a processor configured to: generate a meaning representation corresponding to an input sentence by performing Natural Language Understanding on the input sentence, generate an output sentence corresponding to the input meaning representation based on Recurrent Neural network (RNN), and determine whether the input sentence cannot be processed using the natural language generator. The processor calculates a parameter representing a probability of outputting the input sentence when the meaning representation corresponding to the input sentence is input to the natural language generator, and determines whether the input sentence cannot be processed based on the calculated parameter.