Clock-Offset and Microphone Gain Mismatch Invariant Beamforming

The use of wireless acoustic sensor networks (WASNs) has received increased attention over the last decade. The advantages of WASNs over stand-alone multi-microphone devices are that the microphone array is not anymore limited by the dimensions of a single device, and that microphones can be placed at arbitrary locations. One of the...

Inferring the location of reflecting surfaces exploiting loudspeaker directivity

Accurate sound field reproduction in rooms is often limited by the lack of knowledge of the room characteristics. Information about the room shape or nearby reflecting boundaries can, in principle, be used to improve the accuracy of the reproduction. In this paper, we propose a method to infer the location of nearby reflecting boundaries from...

Rate-constrained noise reduction in wireless acoustic sensor networks

Wireless acoustic sensor networks (WASNs) can be used for centralized multi-microphone noise reduction, where the processing is done in a fusion center (FC). To perform the noise reduction, the data needs to be transmitted to the FC. Considering the limited battery life of the devices in a WASN, the total data rate at which the FC can...

Spatially Correct Rate-Constrained Noise Reduction For Binaural Hearing Aids in Wireless Acoustic Sensor Networks

Compared to monaural hearing aids (HAs), binaural hearing aid systems, in which there is a communication link between the two devices, have improved noise reduction capabilities and the ability to preserve binaural spatial information. However, the limited HA battery lifetime puts constraints on the amount of information that can be shared...

Sensor selection and rate distribution based beamforming in wireless acoustic sensor networks

Power usage is an important aspect of wireless acoustic sensor networks (WASNs) and reducing the amount of information that is to be transmitted is one effective way to save it. In previous contributions, we presented sensor selection as well as rate distribution methods to reduce the power usage of beamforming algorithms in WASNs. Taking...

Distributed Rate-Constrained LCMV Beamforming

In this letter, we propose a decentralized framework for rate-distributed linearly constrained minimum variance (LCMV) beamforming in wireless acoustic sensor networks. To save the energy usage within the network, we propose to minimize the transmission cost and put a constraint on the noise reduction performance. Subsequently, we...

Rate-Distributed Spatial Filtering Based Noise Reduction in Wireless Acoustic Sensor Networks

In wireless acoustic sensor networks (WASNs), sensors typically have a limited energy budget as they are often battery driven. Energy efficiency is therefore essential to the design of algorithms in WASNs. One way to reduce energy costs is to only select the sensors which are most informative, a problem known as sensor selection. In this way,...

A distributed algorithm for robust LCMV beamforming

In this paper we propose a distributed reformulation of the linearly constrained minimum variance (LCMV) beamformer for use in acoustic wireless sensor networks. The proposed distributed minimum variance (DMV) algorithm, for which we demonstrate implementations for both cyclic and acyclic networks, allows the optimal beamformer output to be...

An evaluation of objective measures for intelligibility prediction of time-frequency weighted noisy speech

Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate in cases where noisy speech is processed by a time-frequency weighting. To this end, an extensive evaluation is presented of objective measure for intelligibility prediction of noisy speech...

An evaluation of objective measures for intelligibility prediction of time-frequency weighted noisy speech

Existing objective speech-intelligibility measures are suitable for several types of degradation, however, it turns out that they are less appropriate in cases where noisy speech is processed by a time-frequency weighting. To this end, an extensive evaluation is presented of objective measure for intelligibility prediction of noisy speech...