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HAAQI-Net: A non-intrusive neural music quality assessment model for hearing aids. (arXiv:2401.01145v2 [eess.AS] UPDATED)
cs.LG updates on arXiv.org arxiv.org
This paper introduces HAAQI-Net, a non-intrusive deep learning model for
music quality assessment tailored to hearing aid users. In contrast to
traditional methods like the Hearing Aid Audio Quality Index (HAAQI), HAAQI-Net
utilizes a Bidirectional Long Short-Term Memory (BLSTM) with attention. It
takes an assessed music sample and a hearing loss pattern as input, generating
a predicted HAAQI score. The model employs the pre-trained Bidirectional
Encoder representation from Audio Transformers (BEATs) for acoustic feature
extraction. Comparing predicted scores with ground …
arxiv assessment attention audio audio quality contrast deep learning eess.as hearing index long short-term memory memory music paper quality