14 accepted papers
Modern digital signal processing increasingly leverages multi-channel systems and algorithms to tackle emerging challenges, e.g., in beamforming, crosstalk cancellation (CTC) or active noise control. Commonly, the modeling, design and simulation of these systems involves the use of multiple-input mu…
Measuring personal head-related transfer functions (HRTFs) is essential in binaural audio. Personal HRTFs are not only required for binaural rendering and for loudspeaker-based binaural reproduction using crosstalk cancellation, but they also serve as a basis for data-driven HRTF individualization t…
This paper presents a deep neural network (DNN)-based system for phase reconstruction of speech signals solely from their magnitude spectrograms. The phase is very sensitive to time shifts. Therefore it is meaningful to estimate the phase derivatives instead of the phase directly, e.g., using DNNs a…
Active noise cancellation (ANC) technology is a valuable asset for hearables. For a well performing and robust ANC system precise knowledge of the relevant acoustic paths is vital. It is feasible to individually measure the user’s secondary path by using the inner loudspeaker and microphone that are…
This paper presents a novel 3DoF+ system that allows to navigate, i.e., change position, in scene-based spatial audio content beyond the sweet spot of a Higher Order Ambisonics recording. It is one of the first such systems based on sound capturing at a single spatial position. The system uses a par…
The headphones market is expanding and new applications based on active noise control (ANC) are emerging. In this contribution, we derive a fixed feed-forward FIR filter for ANC headphones based on a minimum mean-square error (MMSE) cost function that realizes user-defined active equalization and at…
Mobile devices for hands-free speech communication often show significant nonlinear distortion in the sound emitted by their loudspeakers. Therefore, conventional linear echo cancellation is not sufficient for maintaining a high conversation quality. In this work we propose a nonlinear echo cancelle…
A novel approach to non-uniform spatial resolution encoding and dimensionality reduction of Higher Order Ambisonics spatial audio content is proposed. Space warping is applied to modify the spatial arrangement of the audio scene such that the coefficient energy is packed in few low order coefficient…
Research in static and time-variant system identification has brought up a broad variety of identification algorithms. In acoustics, e.g., static measurements of transfer functions are commonly conducted using Inverse Cyclic Convolution (ICC) with Exponential Sweep excitation. Identification and tra…
Occluding the ear canal alters the perception of the own voice. This is called the occlusion effect. Low frequency components of the own voice are amplified and high frequency components are attenuated. In this contribution, we extend our previously published Active Occlusion Cancellation (AOC) syst…
Algorithms for Near-End Listening Enhancement (NELE) improve the intelligibility of speech from the far-end, played back in a near-end noisy environment, by adaptively filtering the speech signal and taking into account the near-end background noise characteristics. In contrast to previous works, th…
In system identification one problem is the autocorrelation of the excitation signal which often crucially affects the adaptation process. This paper focuses on the Kalman filter based adaptation working in the frequency domain and the implication due to correlated signal input. Principle simulation…
A drawback of digital transmission of analog signals is the unavoidable quantization error which leads to a limited quality even for good channel conditions. This saturation can be avoided by using analog transmission systems with discrete-time and quasi-continuous-amplitude encoding and decoding, e…
In announcement and communication systems, clean speech is often played back by loudspeakers in the presence of local background noise which decreases intelligibility. Speech reinforcement is a technique that enhances the intelligibility by adaptively filtering the speech, usually based on measured…