A method for performing multi-language communication includes receiving an utterance, identifying a language of the received utterance, determining whether the identified language matches a preset reference language, applying, to the received utterance, an interpretation model interpreting the identified language into the reference language when the identified language does not match the reference language, changing, to text, speech data which is outputted in the reference language as a result of applying the interpretation model, generating a response message responding to the text of the speech data, and outputting the response message. Here, the interpretation model may be a deep neural network model generated through machine learning, and the interpretation model may be stored in an edge device or provided through a server in an Internet of things environment through a 5G network.
METHOD AND APPARATUS FOR PERFORMING MULTI-LANGUAGE COMMUNICATION