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Reverb plays a critical role in music production, where it provides listenerswith spatial realization, timbre, and texture of the music. Yet, it ischallenging to reproduce the musical reverb of a reference music track even byskilled engineers. In response, we propose an end-to-end system capable ofswitching the musical reverb factor of two different mixed vocal tracks. Thismethod enables us to apply the reverb of the reference track to the sourcetrack to which the effect is desired. Further, our model can performde-reverberation when the reference track is used as a dry vocal source. Theproposed model is trained in combination with an adversarial objective, whichmakes it possible to handle high-resolution audio samples. The perceptualevaluation confirmed that the proposed model can convert the reverb factor withthe preferred rate of 64.8%. To the best of our knowledge, this is the firstattempt to apply deep neural networks to converting music reverb of vocaltracks.

Reverb Conversion of Mixed Vocal Tracks Using an End-to-end Convolutional Deep Neural Network