Abstract:
Disclosed is an electronic device. The electronic device includes: a processor, and a memory operatively connected to the processor, the memory stores instructions that, when executed, cause the processor to: select at least one data received through a user input, analyze the selected data, extract additional data based on the analyzed data, learn a personal voice model using the data and the additional data, and provide response data using the personal voice model.
Abstract:
Provided are an electronic device and speech recognition method therefor. The electronic device may include a communication interface to receive speech data from an external electronic device, a memory to store a common language model used by default for speech recognition, a first language model designated for each user, a second language model associated with context information of each user, and a third language model associated with words collected by the electronic device for a preset period of time from the reception time of the speech data; and a processor to perform a procedure of combining at least one of the first language model, the second language model, and the third language model with the common language model to construct an integrated language model, performing speech recognition on the basis of the speech data and the integrated language model, and outputting a speech recognition result corresponding to the speech data.
Abstract:
An electronic device and method are disclosed. The electronic device includes input circuitry, a display, and a processor. The processor implements the method, including extracting at least one piece of context information based at least in part on an application screen displayed on the display, analyzing the extracted at least one piece of context information to generate a language model based on the extracted at least one piece of context information, receiving a voice input of a user through the input circuitry and convert the voice input into a text string using the generated language model, and resetting the generated language model.
Abstract:
A system and method is provided that authenticates a user using hybrid biometrics information, such as a user's image information, a user's voice information, etc. The user authentication method includes: acquiring a number of biometrics information; generating a number of authentication information corresponding to the acquired biometrics information; and performing an integral user authentication based on the by generated authentication information.
Abstract:
A method of performing a voice command function in an electronic device includes detecting voice of a user, acquiring one or more pieces of attribute information from the voice, and authenticating the user by comparing the attribute information with pre-stored authentic attribe information, using a recognition model. An electronic device includes a voice input module configured to detect a voice of a user, a first processor configured to acquire one or more pieces of attribute information from the voice and authenticate the user by comparing the attribute information with a recognition model, and a second processor configured to when the attribute information matches the recognition mode, activate the voice command function, receive a voice command of the user, and execute an application corresponding to the voice command. Other embodiments are also disclosed.
Abstract:
Disclosed is an electronic device including a communication interface, a memory, a microphone, a speaker, a display, a main processor, and a sub-processor activating the main processor by recognizing a wake-up word included in a voice input. The at least one memory stores instructions that, when executed, cause the main processor to receive a first voice input to register the wake-up word, when the first voice input does not include a specified word, to receive a second voice input including a word identical to the first voice input, through the microphone, to generate a wake-up word recognition model for recognizing the wake-up word, and to store the generated wake-up word recognition model in the at least one memory, and when the first voice input includes the specified word, to output information for requesting a third voice input, through the speaker or the display.
Abstract:
Disclosed is an electronic device including processor and memory operatively connected to the processor and storing language model. The electronic device may enter data into the language model, generate an embedding vector in the input embedding layer, add position information to the embedding vector in the positional encoding layer, branch the embedding vector based on domain information, normalize the branched embedding vectors, enter the normalized embedding vectors into the multi-head attention layer, enter output data of the multi-head attention layer into the first layer, normalize pieces of output data of the first layer, enter the normalized pieces of output data of the first layer into the feed-forward layer, enter output data of the feed-forward layer into the second layer and normalize pieces of output data of the second layer, and enter the normalized pieces of output data of the second layer into the linearization layer and the softmax layer to obtain result data. In addition, various embodiments as understood from the specification may be also possible.
Abstract:
Provided are an electronic device and speech recognition method therefor. The electronic device may include a communication interface to receive speech data from an external electronic device, a memory to store a common language model used by default for speech recognition, a first language model designated for each user, a second language model associated with context information of each user, and a third language model associated with words collected by the electronic device for a preset period of time from the reception time of the speech data; and a processor to perform a procedure of combining at least one of the first language model, the second language model, and the third language model with the common language model to construct an integrated language model, performing speech recognition on the basis of the speech data and the integrated language model, and outputting a speech recognition result corresponding to the speech data.