A Multi-Room Transition Dataset for Blind Estimation of Energy Decay - Götz, Philipp; Gotz, Georg; Meyer-Kahlen, Nils; Lee, Kyung Yun; Prawda, Karolina; Habets, Emanuël; Schlecht, Sebastian (2024 18th International Workshop on Acoustic Signal Enhancement (IWAENC), 2024)
We present an acoustic room impulse response dataset focusing on multi-room environments characterized by complex geometries and acoustic conditions. The dataset is accompanied by positional information and visual documentation in the form of 360° photographs. Additionally, we present a method to estimate acoustic energy decay functions from noisy, reverberant speech signals. We demonstrate the effectiveness of the proposed method based on experiments conducted with the presented dataset.
CRIS-Team Scopus Importer:2024-11-01
Keywords: dataset; energy decay functions; Multi-room acoustics

Blind Acoustic Parameter Estimation Through Task-Agnostic Embeddings Using Latent Approximations - Götz, Philipp; Tuna, Cagdas; Brendel, Andreas; Walther, Andreas; Habets, Emanuël (2024 18th International Workshop on Acoustic Signal Enhancement, IWAENC 2024 - Proceedings, 2024)
We present a method for blind acoustic parameter estimation from single-channel reverberant speech. The method is structured into three stages. In the first stage, a variational auto-encoder is trained to extract latent representations of acoustic impulse responses represented as mel-spectrograms. In the second stage, a separate speech encoder is trained to estimate low-dimensional representations from short segments of reverberant speech. Finally, the pre-trained speech encoder is combined with a small regression model and evaluated on two parameter regression tasks. Experimentally, the proposed method is shown to outperform a fully end-to-end trained baseline model.
CRIS-Team Scopus Importer:2024-11-01
Keywords: Blind acoustic parameter estimation; latent approximation

BLIND REVERBERATION TIME ESTIMATION IN DYNAMIC ACOUSTIC CONDITIONS - Götz, Philipp; Tuna, Cagdas; Walther, Andreas; Habets, Emanuël (2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022)
CRIS-Team WoS Importer:2023-01-13

Data-driven local average room transfer function estimation for multi-point equalization - Tuna, Cagdas; Zevering, Annika; Prinn, Albert G.; Götz, Philipp; Walther, Andreas; Habets, Emanuël (Journal of the Acoustical Society of America, 2022)
Multi-point room equalization (EQ) aims to achieve a desired sound quality within a wider listening area than single-point EQ. However, multi-point EQ necessitates the measurement of multiple room impulse responses at a listener position, which may be a laborious task for an end-user. This article presents a data-driven method that estimates a spatially averaged room transfer function (RTF) from a single-point RTF in the low-frequency region. A deep neural network (DNN) is trained using only simulated RTFs and tested with both simulated and measured RTFs. It is demonstrated that the DNN learns a spatial smoothing operation: notches across the spectrum are smoothed out while the peaks of the single-point RTF are preserved. An EQ framework based on a finite impulse response filter is used to evaluate the room EQ performance. The results show that while not fully reaching the level of multi-point EQ performance, the proposed data-driven local average RTF estimation method generally brings improvement over single-point EQ. (C) 2022 Author(s
CRIS-Team WoS Importer:2023-01-13