Abstract:
The present invention relates to a system for editing a text of a portable terminal and a method thereof, and more particularly to a technology which edits a text which is input into a portable terminal based on a touch interface. An exemplary embodiment of the present invention provides a text editing system of a portable terminal, including: an interface unit which inputs or outputs a text or voice; a text generating unit which generates the input text or voice as a text; a control unit which provides a keyboard based editing screen or a character recognition based editing screen for the generated text through the interface unit; and a text editing unit which performs an editing command which is input from a user through the keyboard based editing screen or the character recognition based editing screen under the control of the control unit.
Abstract:
Provided are an apparatus and method for automatic translation, and more specifically, an apparatus and method for automatic translation between low-resource languages lacking learning data. The apparatus includes an inputter configured to receive a source language, which is a low-resource language, and a third language abundant in resources compared to the low-resource language, a memory configured to store a program for performing automatic translation between the source language, which is the low-resource language, and a target language using the third language, and a processor configured to execute the program, wherein the processor performs the automatic translation using a third language vocabulary embedding vector.
Abstract:
Disclosed is a method of editing voice recognition results in a portable device. The method includes a process of converting the voice recognition results into text and displaying the text in a touch panel, a process of recognizing a touch interaction in the touch panel, a process of analyzing an intent of execution of the recognized touch interaction, and a process of editing contents of the text based on the analyzed intent of execution.
Abstract:
Provided are a method and apparatus for constructing a compact translation model that may be installed on a terminal on the basis of a pre-built reference model, in which a pre-built reference model is miniaturized through a parameter imitation learning and is efficiently compressed through a tree search structure imitation learning without degrading the translation performance. The compact translation model provides translation accuracy and speed in a terminal environment that is limited in network, memory, and computation performance.
Abstract:
A real-time utterance verification system according to the present invention includes a speech recognition unit configured to recognize an utterance of an utterer, a memory configured to store a program for verifying the utterance of the utterer in real time, and a processor configured to execute the program stored in the memory, wherein, upon executing the program, the processor generates and stores a list of the utterance of the utterer, performs a semantic analysis on each utterance included in the list, and generates, when the utterance is determined to be an inappropriate utterance for a listener as a result of the semantic analysis, utterance restricting information corresponding to the inappropriate utterance.
Abstract:
A translation verification method using an animation may include the processes of analyzing an originally input sentence in a first language using a translation engine so that the sentence in the first language is converted into a second language, generating an animation capable of representing the meaning of the sentence in the first language based on information on the results of the analysis of the sentence in the first language, and providing the original and the generated animation to a user who uses the original in order for the user to check for errors in the translation.
Abstract:
Provided are a system and method for end-to-end neural machine translation. The method of end-to-end neural machine translation includes performing learning including a READ token on an end-to-end neural machine translation network, performing learning on an action network to learn a position of an actual segmentation point, and performing entire network re-learning on the end-to-end neural machine translation network and the action network.
Abstract:
The present invention relates to a device of simultaneous interpretation based on real-time extraction of an interpretation unit, the device including a voice recognition module configured to recognize voice units as sentence units or translation units from vocalized speech that is input in real time, a real-time interpretation unit extraction module configured to form one or more of the voice units into an interpretation unit, and a real-time interpretation module configured to perform an interpretation task for each interpretation unit formed by the real-time interpretation unit extraction module.
Abstract:
An incremental self-learning based dialogue apparatus for dialogue knowledge includes a dialogue processing unit configured to determine a intention of a user utterance by using a knowledge base and perform processing or a response suitable for the user intention, a dialogue establishment unit configured to automatically learn a user intention stored in a intention annotated learning corpus, store information about the learned user intention in the knowledge base, and edit and manage the knowledge base and the intention annotated learning corpus, and a self-knowledge augmentation unit configured to store a log of a dialogue performed by the dialogue processing unit, detect and classify an error in the stored dialogue log, automatically tag a user intention for the detected and classified error, and store the tagged user intention in the intention annotated learning corpus.
Abstract:
The present invention relates to a translation function and discloses an automatic translation operating device, including: at least one of voice input devices which collects voice signals input by a plurality of speakers and a communication module which receives the voice signals; and a control unit which controls to classify voice signals by speakers from the voice signals and cluster the speaker based voice signals classified in accordance with a predefined condition and then perform voice recognition and translation and a method thereof and a system including the same.