Abstract: A keyword spotting apparatus, method, and computer-readable recording medium are disclosed. The keyword spotting method using an artificial neural network according to an embodiment of the disclosure may include obtaining an input feature map from an input voice; performing a first convolution operation on the input feature map for each of n different filters having the same channel length as the input feature map, wherein a width of each of the filters is w1 and the width w1 is less than a width of the input feature map; performing a second convolution operation on a result of the first convolution operation for each of different filters having the same channel length as the input feature map; storing a result of the second convolution operation as an output feature map; and extracting a voice keyword by applying the output feature map to a learned machine learning model.

Abstract: Systems and techniques to generate imitative responses are illustrated. response generation method performed in an electronic apparatus of the present disclosure includes acquiring at least one piece of utterance data, acquiring a first context corresponding to the utterance data from a context candidate set, generating one or more dialogue sets including the first context and the utterance data, receiving a second context from a user, and acquiring a response corresponding to the second context using a language model based on the one or more dialogue sets.

Abstract: Disclosed is a method of training a dialogue model in an electronic device, the method including selecting a first context from a first dialogue data set including at least one pair of a context and a response corresponding to the context, generating a first response corresponding to the first context through a first dialogue model, generating an augmented dialogue dataset by incorporating a pair of the first context and the first response corresponding to the first context into the first dialogue data set, and training a second dialogue model based on the augmented dialogue dataset.

Abstract: A training method of a conversation model according to various example embodiments of the present disclosure may include identifying a first context, identifying a first response set corresponding to the first context based on a first model, identifying a response subset selected from the first response set based on a gold response corresponding to the first context and training a second model based on the first context information and the response subset.

Abstract: A server may include a communication interface for receiving a plurality of profile information from a plurality of terminals; and a processor configured to divide users of the plurality of terminals into a plurality of groups based on a first criterion, to divide users of a first gender included in each group into a plurality of subgroups based on a second criterion different from the first criterion, to divide users of a second gender different from the first gender, included in each group into a plurality of matching groups to correspond to each of the plurality of subgroups, and to provide profile information of users included in each of the plurality of matching groups corresponding to each of the plurality of subgroups among the plurality of profile information to users included in each of the plurality of subgroups.

Abstract: A keyword spotting apparatus, method, and computer-readable recording medium are disclosed. The keyword spotting method using an artificial neural network according to an embodiment of the disclosure may include obtaining an input feature map from an input voice; performing a first convolution operation on the input feature map for each of n different filters having the same channel length as the input feature map, wherein a width of each of the filters is w1 and the width w1 is less than a width of the input feature map; performing a second convolution operation on a result of the first convolution operation for each of different filters having the same channel length as the input feature map; storing a result of the second convolution operation as an output feature map; and extracting a voice keyword by applying the output feature map to a learned machine learning model.

Abstract: A server may include a communication interface for receiving a plurality of profile information from a plurality of terminals; and a processor configured to divide users of the plurality of terminals into a plurality of groups based on a first criterion, to divide users of a first gender included in each group into a plurality of subgroups based on a second criterion different from the first criterion, to divide users of a second gender different from the first gender, included in each group into a plurality of matching groups to correspond to each of the plurality of subgroups, and to provide profile information of users included in each of the plurality of matching groups corresponding to each of the plurality of subgroups among the plurality of profile information to users included in each of the plurality of subgroups.

Abstract: A spring vent for a tire vulcanizing mold comprises: a sleeve having a flow path vertically passing therethrough; a head opening/closing an inlet at an upper end of the flow path; a rod comprising a bar-type body formed below the head and disposed along the flow path and a stopper formed below the body to be hung to an outside of an outlet at a lower end of the flow path; and a spring inserted into the body. The stopper of the rod is formed to have a spherical shape. An elastic hole having an open bottom is formed in the stopper.

Abstract: A spring vent for a tire vulcanizing mold comprises: a sleeve having a flow path vertically passing therethrough; a head opening/closing an inlet at an upper end of the flow path; a rod comprising a bar-type body formed below the head and disposed along the flow path and a stopper formed below the body to be hung to an outside of an outlet at a lower end of the flow path; and a spring inserted into the body. The stopper of the rod is formed to have a spherical shape. An elastic hole having an open bottom is formed in the stopper.

Abstract: According to example embodiments, a semiconductor material may include zinc, nitrogen, and fluorine. The semiconductor material may further include oxygen. The semiconductor material may include a compound. For example, the semiconductor material may include zinc fluorooxynitride. The semiconductor material may include zinc oxynitride containing fluorine. The semiconductor material may include zinc fluoronitride. The semiconductor material may be applied as a channel material of a thin film transistor (TFT).

Abstract: According to example embodiments, a semiconductor material may include zinc, nitrogen, and fluorine. The semiconductor material may further include oxygen. The semiconductor material may include a compound. For example, the semiconductor material may include zinc fluorooxynitride. The semiconductor material may include zinc oxynitride containing fluorine. The semiconductor material may include zinc fluoronitride. The semiconductor material may be applied as a channel material of a thin film transistor (TFT).

Abstract: According to example embodiments, a transistor may include a gate electrode, a gate insulating layer, and a channel layer stacked on each other; and a source electrode and a drain electrode contacting first and second regions of the channel layer, respectively. The channel layer may include metal oxynitride. The first and second regions of the channel layer may be treated with a plasma containing hydrogen, and the first and second regions have a higher carrier concentration than a carrier concentration of a remaining region of the channel layer. The first and second regions of the channel layer may have a lower oxygen concentration and a higher nitrogen concentration than that of the remaining region thereof. The metal oxynitride of the channel layer may include a zinc oxynitride (ZnON)-based semiconductor.

Abstract: A transistor includes a channel layer including an oxynitride semiconductor doped with at least one of hafnium (Hf) and zirconium (Zr), a source on one side portion of the channel layer and a drain on another side portion of the channel layer, a gate corresponding to the channel layer, and a gate insulation layer between the channel layer and the gate.

Abstract: A transistor may include a channel layer formed of an oxide semiconductor. The oxide semiconductor may include GaZnON, and a proportion of Ga content to a total content of Ga and Zn of the channel layer is about 0.5 to about 4.5 at %.

Abstract: Provided are transistors, methods of manufacturing the same, and electronic devices including the transistors. A transistor includes a channel layer having a multi-layer structure having first and second layers, the first and second semiconductor layers including a plurality of elements having respective concentrations, and the first layer is disposed closer to a gate than the second layer. The second layer has a higher electrical resistance than the first layer as a result of a combination of the elements and of their respective concentrations. At least one of the first and second layers includes a semiconductor material including zinc, oxygen, and nitrogen. One of the first and second layers includes a semiconductor material including zinc fluoronitride. An oxygen content of the second layer is higher than an oxygen content of the first layer. A fluorine content of the second layer is higher than a fluorine content of the first layer.

Abstract: Transistors having sulfur-doped zinc oxynitride channel layers, and methods of manufacturing the same, include a ZnON channel layer with sulfur content ratio with respect to a zinc content of from about 0.1 at % to about 1.2 at %, a source electrode and a drain electrode respectively formed on a first region and a second region of the channel layer, a gate electrode corresponding to the channel layer, and a gate insulation layer between the channel layer and the gate electrode.

Abstract: According to example embodiments, a transistor may include a gate electrode, a gate insulating layer, and a channel layer stacked on each other; and a source electrode and a drain electrode contacting first and second regions of the channel layer, respectively. The channel layer may include metal oxynitride. The first and second regions of the channel layer may be treated with a plasma containing hydrogen, and the first and second regions have a higher carrier concentration than a carrier concentration of a remaining region of the channel layer. The first and second regions of the channel layer may have a lower oxygen concentration and a higher nitrogen concentration than that of the remaining region thereof. The metal oxynitride of the channel layer may include a zinc oxynitride (ZnON)-based semiconductor.

Abstract: According to example embodiments, a semiconductor material may include zinc, nitrogen, and fluorine. The semiconductor material may further include oxygen. The semiconductor material may include a compound. For example, the semiconductor material may include zinc fluorooxynitride. The semiconductor material may include zinc oxynitride containing fluorine. The semiconductor material may include zinc fluoronitride. The semiconductor material may be applied as a channel material of a thin film transistor (TFT).

Abstract: According to example embodiments, a semiconductor material may include zinc, nitrogen, and fluorine. The semiconductor material may further include oxygen. The semiconductor material may include a compound. For example, the semiconductor material may include zinc fluorooxynitride. The semiconductor material may include zinc oxynitride containing fluorine. The semiconductor material may include zinc fluoronitride. The semiconductor material may be applied as a channel material of a thin film transistor (TFT).