6 accepted papers
Audio-visual speech enhancement (AVSE) methods use both audio and visual features for the task of speech enhancement and the use of visual features has been shown to be particularly effective in multi-speaker scenarios. In the majority of deep neural network (DNN) based AVSE methods, the audio and v…
We refer to direction-of-arrivals (DOAs) estimation of a user-defined subset of directional (desired) sound sources as signal-aware DOA estimation. Source selection, thereby, can be achieved with time-frequency masks to apply attention to TF bins dominated by desired sources. With deep neural networ…
Flexible spatial sound capturing and reproduction can be achieved with multiple microphones by using linear spatial filtering or non-linear parametric processing. The non-linear approaches usually provide a superior spatial resolution compared to the linear approaches but can result in artifacts due…
We present a spatial matrix filtering framework for noise reduction in the spherical harmonics (ambisonics) domain (SHD), which outputs an SHD signal vector rather than one signal as commonly provided by beamforming approaches. We discuss two spatial matrix filtering methods: A multi-beamformer meth…
Outdoor recordings of speech are often corrupted by wind noise, which is difficult to reduce due to its high non-stationarity. In this work, a multi-channel wind noise reduction method is presented, based on a joint estimation of the speech and wind noise power spectral densities. In contrast to exi…
A weighted least squares beam shaping technique for sound field control using a loudspeaker array is proposed. Given a desired spatial response at prescribed control points, the space-time filter is designed by solving a least squares minimization problem. To reduce the computational effort, we prop…