Speech signal processing

Investigating the Learnable Components of the LEArnable Front-end (LEAF) and Adapting its Per-Channel Energy Normalisation (PCEN) for Noisy Conditions

Only the Per-Channel Energy Normalisation (PCEN) layer of the LEArnable Front-end (LEAF) model learns during training, while the Gabor filterbank and Gaussian low-pass filters remain unchanged. Adapting the PCEN layer using a small amount of noisy data can improve the performance of a LEAF model trained on clean speech when deployed in noisy environments.

Investigating the Learnable Components of the LEArnable Front-end (LEAF) and Adapting its Per-Channel Energy Normalisation (PCEN) for Noisy Conditions

Interpreting End-to-End Deep Learning Models for Speech Source Localization Using Layer-wise Relevance Propagation