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Virtual 3-D sound can be easily delivered to a listener by binaural audio signals that are reproduced via headphones, which guarantees that only the correct signals reach the corresponding ears. Reproducing the binaural audio signal by two or more loudspeakers introduces the problems of crosstalk on the one hand, and, of reverberation on the other hand. In(More)
The human auditory system is very well matched to both human speech and environmental sounds. Therefore, the question arises whether human speech material may provide useful information for training systems for analyzing nonspeech audio signals, such as in a recognition task. To find out how similar nonspeech signals are to speech, we measure the closeness(More)
In listening room compensation, the aim is to compensate for the degradations that are rendered to an audio signal by transmission in a closed room. Due to multiple reflections of the soundwaves, the listener receives a superposition of delayed and attenuated versions of the source signal. A filter is designed so that the convolution of the room impulse(More)
In this paper, we propose to use the scaling ambiguity of convolutive blind source separation for shortening the unmixing filters. An often used approach for separating convolutive mixtures is the transformation to the time-frequency domain where an instantaneous ICA algorithm can be applied for each frequency separately. This approach leads to the so(More)
The purpose of room impulse response reshaping is to reduce reverberation and thus to improve the perceived quality of the received signal by prefiltering the source signal before it is played with a loudspeaker. The filter design is usually carried out by solving an optimization problem. There are, in general, two possibilities to improve the robustness of(More)
In this paper, we present a new algorithm for solving the permutation ambiguity in convolutive blind source separation. Transformed to the frequency domain, existing algorithms can efficiently solve the reduction of the source separation problem into independent instantaneous separation in each frequency bin. However, this independency leads to the problem(More)
Despite the success of the automatic speech recognition framework in its own application field, its adaptation to the problem of acoustic event detection has resulted in limited success. In this paper, instead of treating the problem similar to the segmentation and classification tasks in speech recognition, we pose it as a regression task and propose an(More)
For the separation of convolutive mixtures, an often used approach is the transformation to the time-frequency domain, where the problem is reduced to multiple instantaneous mixtures. This allows for the employment of well-known ICA algorithms. The drawbacks of this method are the inherent permutation and scaling problems. These ambiguities have to be(More)
By using room impulse response shortening and shaping it is possible to reduce the reverberation effects and therefore improve speech intelligibility. This may be achieved by a prefilter that modifies the overall impulse response to have a stronger attenuation. For achieving a spatial robustness, multichannel approaches have been proposed. Unfortunately,(More)