Abstract:
A method of updating speech recognition data including a language model used for speech recognition, the method including obtaining language data including at least one word; detecting a word that does not exist in the language model from among the at least one word; obtaining at least one phoneme sequence regarding the detected word; obtaining components constituting the at least one phoneme sequence by dividing the at least one phoneme sequence into predetermined unit components; determining information regarding probabilities that the respective components constituting each of the at least one phoneme sequence appear during speech recognition; and updating the language model based on the determined probability information.
Abstract:
A speech recognition method and a speech recognition apparatus which pre-download a speech recognition model predicted to be used and use the speech recognition model in speech recognition is provided. The speech recognition method, performed by the speech recognition apparatus, includes determining a speech recognition model, based on user information downloading the speech recognition model, performing speech recognition, based on the speech recognition model, and outputting a result of performing the speech recognition.
Abstract:
A method of updating speech recognition data including a language model used for speech recognition, the method including obtaining language data including at least one word; detecting a word that does not exist in the language model from among the at least one word; obtaining at least one phoneme sequence regarding the detected word; obtaining components constituting the at least one phoneme sequence by dividing the at least one phoneme sequence into predetermined unit components; determining information regarding probabilities that the respective components constituting each of the at least one phoneme sequence appear during speech recognition; and updating the language model based on the determined probability information.
Abstract:
A method of updating speech recognition data including a language model used for speech recognition, the method including obtaining language data including at least one word; detecting a word that does not exist in the language model from among the at least one word; obtaining at least one phoneme sequence regarding the detected word; obtaining components constituting the at least one phoneme sequence by dividing the at least one phoneme sequence into predetermined unit components; determining information regarding probabilities that the respective components constituting each of the at least one phoneme sequence appear during speech recognition; and updating the language model based on the determined probability information.
Abstract:
A method of updating speech recognition data including a language model used for speech recognition, the method including obtaining language data including at least one word; detecting a word that does not exist in the language model from among the at least one word; obtaining at least one phoneme sequence regarding the detected word; obtaining components constituting the at least one phoneme sequence by dividing the at least one phoneme sequence into predetermined unit components; determining information regarding probabilities that the respective components constituting each of the at least one phoneme sequence appear during speech recognition; and updating the language model based on the determined probability information.
Abstract:
A method of updating speech recognition data including a language model used for speech recognition, the method including obtaining language data including at least one word; detecting a word that does not exist in the language model from among the at least one word; obtaining at least one phoneme sequence regarding the detected word; obtaining components constituting the at least one phoneme sequence by dividing the at least one phoneme sequence into predetermined unit components; determining information regarding probabilities that the respective components constituting each of the at least one phoneme sequence appear during speech recognition; and updating the language model based on the determined probability information.
Abstract:
An electronic device and method for providing a translations service are disclosed. The electronic device for providing a translation service includes an input unit comprising input circuitry configured to receive input text of a first language, a processor configured to divide the input text into a main segment and a sub-segment and to generate output text of a second language by selecting translation candidate text corresponding to the input text from translation candidate text of the second language, based on a meaning of text included in the sub-segment, and an output unit comprising output circuitry configured to output the output text.
Abstract:
Provided are methods of aging an x-ray generator having carbon nanotube electron emitters. The method of aging an x-ray generator that includes a cathode, a gate electrode, and an anode, includes applying a desired, or alternatively predetermined anode voltage to the anode, and applying a direct current pulse voltage to the gate electrodes to emit electrons from electron emitters. The method further includes maintaining an anode current formed by electrons generated from the electron emitters constant.
Abstract:
A mesh electrode adhesion structure includes: a substrate, and an opening defined in the substrate; a mesh electrode on the substrate, and a first combination groove defined in the mesh electrode; and an adhesion layer between the substrate and the mesh electrode. The mesh electrode includes: a mesh region corresponding to the opening defined in the substrate, and an adhesion region in which the first combination groove exposes the adhesion layer.
Abstract:
Provided herein is a voice recognition server and a control method thereof, the method including determining an index value for each of a plurality of training texts; setting a group for each of the plurality of training texts based on the index values of the plurality of training texts, and matching a function corresponding to each group and storing the matched results; in response to receiving a user's uttered voice from a user terminal apparatus, determining an index value from the received uttered voice; and searching a group corresponding to the index value determined from the received uttered voice, and performing the function corresponding to the uttered voice, thereby providing a voice recognition result of a variety of user's uttered voices suitable to the user's intentions.