Speech enhancement and separation are core problems in audio signal processing, with
commercial applications in devices as diverse as mobile phones, conference call systems …

The ability to localize and track acoustic events is a fundamental prerequisite for equip**
machines with the ability to be aware of and engage with humans in their surrounding …

Imagine being in a crowded room with a cacophony of speakers and having the ability to
focus on or remove speech from a specific 2D region. This would require understanding and …

Optimization of a microphone array geometry has an important impact on the beamforming
performance. Though the environment settings may change in time, microphone locations …

Multichannel speech enhancement systems are capable of extracting desired signals from
noisy microphone signals. Optimal spatial filters used for source extraction often require …

Sparsity-based blind source separation (BSS) algorithms in the short time-frequency (TF)
domain have received a lot of attention due to their versatility and noise reduction …

As we are surrounded by an increased number of mobile devices equipped with wireless
links and multiple microphones, eg, smartphones, tablets, laptops, and hearing aids, using …

Many multi-microphone speech enhancement algorithms require the relative transfer
function (RTF) vector of the desired speech source, relating the acoustic transfer functions of …

The problem of blind separation of speech signals in the presence of noise using multiple
microphones is addressed. Blind estimation of the acoustic parameters and the individual …

A blind source separation technique in noisy environment is proposed based on spectral
masking and minimum variance distortionless response (MVDR) beamformer (BF) …