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Hands-free acquisition of speech is required in many human-machine interfaces and communication systems. The signals received by integrated microphones contain a desired speech signal, spatially coherent interfering signals, and background noise. In order to enhance the desired speech signal, state-of-the-art techniques apply data-dependent spatial filters(More)
Extracting desired source signals in noisy and reverberant environments is required in many hands-free communication systems. In practical situations, where the position and number of active sources may be unknown and time-varying, conventional implementations of spatial filters do not provide sufficiently good performance. Recently, informed spatial(More)
—We extend Tone Reservation for peak-to-average ratio reduction in MIMO-multiuser OFDM scenarios. First, we consider a multiuser BC (broadcast) situation where a precoding is applied at every carrier. This is considered to be a very demanding situation for peak-to-average ratio reduction. Tellado's Tone Reservation, however, is especially suited for this(More)
In noise reduction, a common approach is to use a microphone array with a beamformer that combines the individual microphone signals to extract a desired speech signal. The beamformer weights usually depend on the statistics of the noise and desired speech signals, which cannot be directly observed and must be estimated. Estimators based on the speech(More)
Sound acquisition in noisy and reverberant conditions where the acoustic scene changes rapidly remains a challenging task. In this work, we consider the problem of obtaining a desired, arbitrary spatial response for at most L sound sources being simultaneously active per time-frequency instant. We propose a minimum mean-squared error spatial filter that(More)