Exploiting Time-Frequency Conformers for Music Audio Enhancement
Yunkee Chae Junghyun Koo Sungho Lee Kyogu Lee
With the proliferation of video platforms on the internet, recording musical
performances by mobile devices has become commonplace. However, these
recordings often suffer from degradation such as noise and reverberation, which
negatively impact the listening experience. Consequently, the necessity for
music audio enhancement (referred to as music enhancement from this point
onward), involving the transformation of degraded audio recordings into
pristine high-quality music, has surged to augment the auditory experience. To
address this issue, we propose a music enhancement system based on the
Conformer architecture that has demonstrated outstanding performance in speech
enhancement tasks. Our approach explores the attention mechanisms of the
Conformer and examines their performance to discover the best approach for the
music enhancement task. Our experimental results show that our proposed model
achieves state-of-the-art performance on single-stem music enhancement.
Furthermore, our system can perform general music enhancement with multi-track
mixtures, which has not been examined in previous work.