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We investigate the objective performance of five high-end commerciallyavailable Hearing Aid (HA) devices compared to DNN-based speech enhancementalgorithms in complex acoustic environments. To this end, we measure the HRTFsof a single HA device to synthesize a binaural dataset for training twostate-of-the-art causal and non-causal DNN enhancement models. We then generatean evaluation set of realistic speech-in-noise situations using an Ambisonicsloudspeaker setup and record with a KU100 dummy head wearing each of the HAdevices, both with and without the conventional HA algorithms, applying the DNNenhancers to the latter. We find that the DNN-based enhancement outperforms theHA algorithms in terms of noise suppression and objective intelligibilitymetrics.

An objective evaluation of Hearing Aids and DNN-based speech enhancement in complex acoustic scenes