Blind Acoustic Parameter Estimation Through Task-Agnostic Embeddings Using Latent Approximations - Götz, Philipp; Tuna, Cagdas; Brendel, Andreas; Walther, Andreas; Habets, Emanuël (2024 18th International Workshop on Acoustic Signal Enhancement, IWAENC 2024 - Proceedings, 2024)
We present a method for blind acoustic parameter estimation from single-channel reverberant speech. The method is structured into three stages. In the first stage, a variational auto-encoder is trained to extract latent representations of acoustic impulse responses represented as mel-spectrograms. In the second stage, a separate speech encoder is trained to estimate low-dimensional representations from short segments of reverberant speech. Finally, the pre-trained speech encoder is combined with a small regression model and evaluated on two parameter regression tasks. Experimentally, the proposed method is shown to outperform a fully end-to-end trained baseline model.
CRIS-Team Scopus Importer:2024-11-01
Keywords: Blind acoustic parameter estimation; latent approximation