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pro vyhledávání: '"Tesch, Kristina"'
Single-channel speech separation is a crucial task for enhancing speech recognition systems in multi-speaker environments. This paper investigates the robustness of state-of-the-art Neural Network models in scenarios where the pitch differences betwe
Externí odkaz:
http://arxiv.org/abs/2407.15749
Autor:
Tesch, Kristina, Gerkmann, Timo
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.32, pp. 542-553, 2024
In a multi-channel separation task with multiple speakers, we aim to recover all individual speech signals from the mixture. In contrast to single-channel approaches, which rely on the different spectro-temporal characteristics of the speech signals,
Externí odkaz:
http://arxiv.org/abs/2304.12023
Autor:
Tesch, Kristina, Gerkmann, Timo
Publikováno v:
ICASSP 2023 - IEEE International Conference on Acoustics, Speech and Signal Processing
In a scenario with multiple persons talking simultaneously, the spatial characteristics of the signals are the most distinct feature for extracting the target signal. In this work, we develop a deep joint spatial-spectral non-linear filter that can b
Externí odkaz:
http://arxiv.org/abs/2211.02420
Autor:
Tesch, Kristina, Gerkmann, Timo
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 563-575, 2023
The key advantage of using multiple microphones for speech enhancement is that spatial filtering can be used to complement the tempo-spectral processing. In a traditional setting, linear spatial filtering (beamforming) and single-channel post-filteri
Externí odkaz:
http://arxiv.org/abs/2206.13310
Employing deep neural networks (DNNs) to directly learn filters for multi-channel speech enhancement has potentially two key advantages over a traditional approach combining a linear spatial filter with an independent tempo-spectral post-filter: 1) n
Externí odkaz:
http://arxiv.org/abs/2206.11181
Autor:
Tesch, Kristina, Gerkmann, Timo
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing, Vol. 29, 2021
The majority of multichannel speech enhancement algorithms are two-step procedures that first apply a linear spatial filter, a so-called beamformer, and combine it with a single-channel approach for postprocessing. However, the serial concatenation o
Externí odkaz:
http://arxiv.org/abs/2104.11033
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