Marco Jeub

A binaural room impulse response database for the evaluation of dereverberation algorithms

This paper describes a new database of binaural room impulse responses (BRIR), referred to as the Aachen Impulse Response (AIR) database. The main field of application of this database is the evaluation of speech enhancement algorithms dealing with room reverberation. The measurements with a dummy head took place in a low-reverberant studio booth, an office room, a meeting room and a lecture room. Due to the different dimensions and acoustic properties, it covers a wide range of situations where digital hearing aids or other hands-free devices can be used. Besides the description of the database, a motivation for using binaural instead of monaural measurements is given. Furthermore an example using a coherence-based dereverberation technique is provided to show the advantage of this database for algorithm evaluation. The AIR database is being made available online.

Model-Based Dereverberation Preserving Binaural Cues

The ability of the human auditory system for sound localization mainly depends on the binaural cues, especially interaural time and level differences (ITD and ILD). In the context of digital hearing aids and binaural audio transmission systems, these cues can be severely degraded by independent bilateral signal processing such as dereverberation or noise reduction. This contribution presents a novel two-stage binaural dereverberation algorithm which explicitly preserves the binaural cues. The first stage is based on a statistical model of the room impulse responses (RIR) and comprises a spectral subtraction rule which reduces late reverberation only. It includes a smoothing process of the spectral gains to reduce musical tones. In a second stage, the residual reverberation is attenuated by a dual-channel Wiener filter. This is derived from a coherence model of the reverberant sound field taking into account shadowing effects of the head. The overall binaural-input binaural-output structure efficiently reduces both early and late reverberation. In experiments as well as informal listening tests using measured binaural room impulse responses, the proposed algorithm significantly improves speech quality according to objective and subjective measures.

Noise reduction for dual-microphone mobile phones exploiting power level differences

This paper discusses the application of noise reduction algorithms for dual-microphone mobile phones. An analysis of the acoustical environment based on recordings with a dual-microphone mock-up phone mounted on a dummy head is given. Motivated by the recordings, a novel dual-channel noise reduction algorithm is proposed. The key components are a noise PSD estimator and an improved spectral weighting rule which both explicitly exploit the Power Level Differences (PLD) of the desired speech signal between the microphones. Experiments with recorded data show that this low complexity system has a good performance and is beneficial for an integration into future mobile communication devices.

A Semi-Analytical Model for the Binaural Coherence of Noise Fields

A novel semi-analytical signal processing model for the binaural coherence of homogeneous isotropic noise fields is presented in this contribution. This is derived from a simplified geometrical model of the human head, where the shadowing between the left and right ear is modeled by two nonreflecting circular plates. Based on Kirchhoffs diffraction theory, it is shown how the corresponding coherence is calculated. This model can be used as part of various binaural signal processing algorithms, such as speech enhancement for digital hearing aids or binaural speech transmission systems. In experiments using an artificial head in a highly reverberant environment, it is confirmed that the proposed theoretical model shows a good match with the coherence obtained from measurements.

Binaural dereverberation based on a dual-channel Wiener filter with optimized noise field coherence

In this paper a novel speech enhancement algorithm for binaural dereverberation is proposed. It is based on a multichannel Wiener filter approach, which is optimized for the application to digital hearing aids and binaural telephony headsets. This is mainly done by two different modifications. First, an optimized model for the binaural coherence which takes the shadowing effects of the head into account. Second, a binaural input-output structure which does not affect the most important binaural cues, i.e., interaural time difference (ITD) and interaural level difference (ILD), and hence, keeps the localization ability. Evaluations with measured binaural room impulse responses (BRIR) show that this approach is capable of reducing reverberation especially in highly reverberant environments.

Active noise control in headsets: A new approach for broadband feedback ANC

In this paper a novel approach for broadband feedback active noise control (ANC) is presented which is based on the combination of classical non-adaptive feedback and adaptive feedback ANC techniques. The non-adaptive part is suitable to attenuate low frequency ambient noise whereas the adaptive part attenuates periodic components of the ambient noise. The proposed technique yields a higher overall noise attenuation performance compared to a purely classical non-adaptive feedback or purely adaptive feedback ANC system. In addition to that, the combination of both techniques is also beneficial for practical realizations since the adaptive feedback ANC stabilizes the overall system. With regard to low cost headset devices, the impact of practical hardware constraints such as low-cost analog-to-digital and digital-to-analog converters (ADC, DAC) is discussed. As a conclusion, a mixed analog-digital realization of the new approach is proposed.

Enhancement of reverberant speech using the CELP postfilter

In this paper we investigate the application of adaptive postfiltering for the enhancement of reverberant speech. The considered method is commonly used in Code Excited Linear Prediction (CELP) speech coding to lower the impact of quantization noise in the excitation signal and the spectral envelope. We show that the underlying additive noise model is accurate enough to enhance speech which is recorded in an enclosed space where the resulting early reflections are usually modeled as a convolutive distortion. By means of adaptive filtering, the amplitudes of the unwanted peaks in the excitation signal are attenuated and the signal components at the harmonic peaks are emphasized. Both, single- and multi-channel dereverberation algorithms are proposed having a moderate computational complexity. Experiments have shown that this approach is capable of reducing early reverberation and attenuate the “distance-effect” arising from room reflections.

Advanced H.264/AVC encoder optimizations on a TMS320DM642 digital signal processor

This paper discusses the optimization of the H.264/AVC video encoder in the context of a modified software implementation on a Texas Instruments TMS320DM642 digital signal processor. Several algorithmic optimizations are proposed to improve time critical parts of the codec like the quantization step and the pixel interpolation. The algorithms proposed in this paper invoke the Enhanced Direct Memory Access (EDMA) Controller, intrinsics and look-up tables to accelerate the encoding and do not affect the image Peak Signal-to-Noise Ratio (PSNR) or compression performance. The computational acceleration gain of these algorithms are the foundation of our real time 30 CIF frames/second baseline implementation.