5 accepted papers
Acoustic beamforming is crucial for many applications where ex-traction of a target signal from a noisy environment is required. In order to implement practical beamformers, e.g. the multichannel Wiener filter (MWF), estimation of the target and noise power spectral densities (PSDs), and the relativ…
In headset and hearing aid applications, it is of interest to retrieve the user's own voice in a noisy environment, e.g. for telephony applications. To do so, the cross-power spectral density (CPSD) of the interference-plus-noise is required. In this paper, a novel maximum likelihood (ML) estimator…
We propose a non-intrusive intelligibility measure for noisy and non-linearly processed speech, i.e. a measure which can predict intelligibility from a degraded speech signal without requiring a clean reference signal. The proposed measure is based on the Short-Time Objective Intelligibility (STOI)…
We propose and evaluate a binaural speech intelligibility measure. The measure is a binaural extension of the Short-Time Objective Intelligibility (STOI) measure and focuses on predicting the intelligibility of noisy speech which has been enhanced by a speech processing algorithm (e.g. in a hearing…
This work focuses on an adaptive beamformer in a hearing aid application using a generalized sidelobe canceller structure (GSC). In this application, the constraint and blocking matrices in the GSC structure are specifically designed using an estimate of the transfer functions between the target sou…