Disclosed is an artificial intelligence (AI)-based voice sampling apparatus for providing a speech style in a heterogeneous label, including a rhyme encoder configured to receive a user's voice, extract a voice sample, and analyze a vocal feature included in the voice sample, a text encoder configured to receive text for reflecting the vocal feature, a processor configured to classify the voice sample input to the rhythm encoder into a label according to the vocal feature, provide a weight by measuring a distance between a voice sample corresponding to the label and a voice sample corresponding to a heterogeneous label as a label other than the label and provide a weight by measuring similarity between the label and the heterogeneous label, extract an embedding vector representing the vocal feature, generate a speech style from the embedding vector, and apply the generated speech style to the text, and a rhyme decoder configured to output synthesized voice data in which the speech style is applied to the text by the processor.
Artificial intelligence (AI)-based voice sampling apparatus and method for providing speech style in heterogeneous label