Jan Ole Jungmann

Combined Acoustic MIMO Channel Crosstalk Cancellation and Room Impulse Response Reshaping

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 crosstalk cancellation, the audio signals are fed through a network of prefilters prior to loudspeaker reproduction to ensure that only the designated signal reaches the corresponding ear of the listener. Since room impulse responses are very sensitive to spatial mismatch, and since listeners might slightly move while listening, robust designs are needed. In this paper, we present a method that jointly handles the three problems of crosstalk, reverberation reduction, and spatial robustness with respect to varying listening positions for one or more binaural source signals and multiple listeners. The proposed method is based on a multichannel room impulse response reshaping approach by optimizing a -norm based criterion. Replacing the well-known least-squares technique by a -norm based method employing a large value for allows us to explicitly control the amount of crosstalk and to shape the remaining reverberation effects according to a desired decay.

On CUDA implementation of a multichannel room impulse response reshaping algorithm based on p-norm optimization

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, these approaches suffer from a very high computational cost and are far too slow for being of practical use in applications where filters have to be designed in real-time. In this work we tackle this drawback using a CUDA implementation and achieve a speedup of over 130 times.

A study on speech quality and speech intelligibility measures for quality assessment of single-channel dereverberation algorithms

This paper reports on the evaluation of several objective quality measures for predicting the quality of the dereverberated speech signals. The correlations between subjective quality assessment for single-channel dereverberation techniques and objective speech quality as well as speech intelligibility measures are analyzed and discussed. Six different single-channel dereverberation algorithms were included in the evaluation to account for different types of distortions. The subjective quality was assessed along the four attributes reverberant, colored, distorted and overall quality following the recommendations of ITU-T P.835. The objective measures included system-based, i.e. channel-based, as well as signal-based measures.

Subjective speech quality and speech intelligibility evaluation of single-channel dereverberation algorithms

In this contribution, six different single-channel dereverberation algorithms are evaluated subjectively in terms of speech intelligibility and speech quality. In order to study the influence of the dereverberation algorithms on speech intelligibility, speech reception thresholds in noise were measured for different reverberation times. The quality ratings were obtained following the ITU-T P.835 recommendations (with slight changes for adaptation to the problem of dere-verberation) and included assessment of the attributes: reverberant, colored, distorted, and overall quality. Most of the algorithms improved speech intelligibility for short as well as long reverberation times compared to the reverberant condition. The best performance in terms of speech intelligibility and quality was observed for the regularized spectral inverse approach with pre-echo removal. The overall quality of the processed signals was highly correlated with the attribute reverberant or/and distorted. To generalize the present outcomes, further studies are needed to account for the influence of the estimation errors.

Perturbation of room impulse responses and its application in robust listening room compensation

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 the equalizers against small movements of the listener and/or receiver; namely multi-position approaches or the utilization of a regularization term. Multi-position approaches suffer from the extensive effort of measuring multiple room impulse responses. Stochastic models may describe the average system error due to spatial mismatch, but only quadratic penalty terms have been considered so far. In this contribution we propose a third method to improve robustness against spatial misalignment. We combine the two approaches by generating multiple realizations of distorted room impulse responses and feeding them into the multiposition algorithm. Based on our previous work, we propose a model to capture the perturbations with respect to the assumed displacement.

Optimized gradient calculation for room impulse response reshaping algorithm based on p-norm optimization

By using room impulse response shortening and reshaping it is possible to reduce the reverberation effects and therefore improve the perceived quality. This may be achieved by a prefilter that modifies the overall impulse response to have a faster decay. The traditional filter shortening approach using least-squares methods is fast and directly computable, but it suffers from late echoes. Newer approaches using the p-norm overcome this drawback but are computationally very demanding, as the optimization process uses a gradient-descent approach with slow convergence. In this work we propose a modification to this approach that results in a significantly faster convergence. With this modification, the algorithm is less likely to be trapped in a local minimum and therefore also leads to a better convergence point. The method will be demonstrated on simulated and real-world room impulse responses.

Automated drill-stop by SVM classified audible signals

Neuroscience research often requires direct access to brain tissue in animal models which clearly requires opening of the protective cranium. Minimizing animal numbers requests only well-experienced surgeons, since clumsy performance may lead to premature death of the animal. To minimise those traumatic outcomes, an algorithmic approach for closed-loop control of our Spherical Assistant for Stereotaxic Surgery (SASSU) was designed. Controlling the surgical robots micro-drill unit by audio pattern recognition proved to be a simple and reliable way to automatically stop the automated drill feed. Sound analysis based on the anatomical morphology of a rat skull was used to train a Support Vector Machine (SVM) classification of the time-frequency representations of the drill sound. Fully automated high throughput animal surgeries are the goal of this approach.

Robust combined crosstalk cancellation and listening-room compensation

Crosstalk cancellation is a well-known technique to deliver virtual 3D sound to a listener via two or more loudspeakers. In this method, the binaural source signals are processed with a network of prefilters prior to loudspeaker reproduction in order to ensure that only the prescribed source signals reach the corresponding ears of the listener, such that all acoustic crosstalk is cancelled out and no significant reverberation is present. Since listeners might slightly move their heads within a certain range while listening, robust designs are needed. In this paper, we propose a method for the robust design of crosstalk cancellers in which we replace known least-squares techniques by a p-norm optimization that allows us to explicitly control the amount of crosstalk and shape the remaining reverberation effects according to a desired decay.

JOINT TIME-DOMAIN RESHAPING AND FREQUENCY-DOMAIN EQUALIZATION OF ROOM IMPULSE RESPONSES

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 response and the equalizer contains better acoustic properties than the original acoustic channel. Common approaches for derever-beration optimize only the time-domain representation of the overall impulse response and may introduce distortions in the frequency domain. Equalization of the frequency response, on the other hand, often does not consider the time-domain behavior in an ideal way. In this paper, we propose a novel method to jointly consider both the time- and frequency-domain behavior. It outperforms the methods known from literature in terms of dereverberation and equalization performance. Results are presented for a room impulse response measured in a real living room.

A new clustering approach for solving the permutation problem in convolutive blind source separation

In this paper we propose a new clustering approach for solving the permutation ambiguity in convolutive blind source separation. After the transformation to the time-frequency domain, the problem of separation of sources can be reduced to multiple instantaneous problems, which may be solved using independent component analysis. The drawbacks of this approach are the inherent permutation and scaling ambiguities, which have to be corrected before the transformation to the time domain. Here, we propose a new method that allows for aligning up to several hundreds of consecutive bins into clusters. The depermutation of these clusters using some known techniques is then much easier than the original problem. The performance of the proposed method is evaluated on real-room recordings.