Abstract: An operation method of a dialog agent includes obtaining an utterance history including at least one of an outgoing utterance to be transmitted to request a service or at least one of an incoming utterance to be received to request the service, updating a requirement specification including items requested for the service based on the utterance history, generating utterance information to be used to request the service based on the updated requirement specification, and outputting the generated utterance information.

Abstract: A method and computing device with classification verification is provided. A processor-implemented method includes implementing a classification neural network to generate a classification result of data input to the classification neural network by generating, with respect to the input data, intermediate hidden values of one or more hidden layers of the classification neural network, generating the classification result of the input data based on the generated intermediate hidden values, and generating a determination of a reliability of the classification result by implementing a verification neural network, input the intermediate hidden values, to generate the determination of the reliability.

Abstract: An operation method of a dialog agent includes obtaining an utterance history including at least one of an outgoing utterance to be transmitted to request a service or at least one of an incoming utterance to be received to request the service, updating a requirement specification including items requested for the service based on the utterance history, generating utterance information to be used to request the service based on the updated requirement specification, and outputting the generated utterance information.

Abstract: A processor-implemented classification method includes: determining a first probability vector including a first probability, for each of a plurality of classes, resulting from a classification of an input with respect to the classes; determining, based on the determined first probability vector, whether one or more of the classes represented in the first probability vector are confusing classes; adjusting, in response to one or more of the classes being the confusing classes, the determined first probability vector based on a first probability of each of the confusing classes and a maximum value of the first probabilities; determining a second probability vector including a second probability, for each of the classes, resulting from another classification of the input with respect to the classes; and performing classification on the input based on a result of a comparison between the determined second probability vector and the adjusted first probability vector.

Abstract: An operation method of a dialog agent includes obtaining an utterance history including at least one of an outgoing utterance to be transmitted to request a service or at least one of an incoming utterance to be received to request the service, updating a requirement specification including items requested for the service based on the utterance history, generating utterance information to be used to request the service based on the updated requirement specification, and outputting the generated utterance information.

Abstract: A processor-implemented classification method includes: determining a first probability vector including a first probability, for each of a plurality of classes, resulting from a classification of an input with respect to the classes; determining, based on the determined first probability vector, whether one or more of the classes represented in the first probability vector are confusing classes; adjusting, in response to one or more of the classes being the confusing classes, the determined first probability vector based on a first probability of each of the confusing classes and a maximum value of the first probabilities; determining a second probability vector including a second probability, for each of the classes, resulting from another classification of the input with respect to the classes; and performing classification on the input based on a result of a comparison between the determined second probability vector and the adjusted first probability vector.

Abstract: Disclosed is an operation method of a neural network including a first network and a second network, the method including acquiring state information output from the first network based on input information, determining whether the state information satisfies a condition using the second network, iteratively applying the state information to the first network in response to determining that the state information does not satisfy the condition, and outputting the state information in response to determining that the state information satisfy the condition.

Abstract: An operation method of a dialog agent includes obtaining an utterance history including at least one of an outgoing utterance to be transmitted to request a service or at least one of an incoming utterance to be received to request the service, updating a requirement specification including items requested for the service based on the utterance history, generating utterance information to be used to request the service based on the updated requirement specification, and outputting the generated utterance information.