Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Tang, Zhenyu"'
We present a novel approach to improve the performance of learning-based speech dereverberation using accurate synthetic datasets. Our approach is designed to recover the reverb-free signal from a reverberant speech signal. We show that accurately si
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4fe7fad781050047f8c6d95f62daa8b
http://arxiv.org/abs/2212.05360
http://arxiv.org/abs/2212.05360
Publikováno v:
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
We present a neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment. Our FAST-RIR takes rectangular room dimensions, listener and speaker positions, a
We present the Geometric-Wave Acoustic (GWA) dataset, a large-scale audio dataset of about 2 million synthetic room impulse responses (IRs) and their corresponding detailed geometric and simulation configurations. Our dataset samples acoustic environ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c92558e6eb6d627621e01bd07919567
Deep neural networks have recently shown great success in the task of blind source separation, both under monaural and binaural settings. Although these methods were shown to produce high-quality separations, they were mainly applied under offline se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6630f941bc4f6bb7eefdb3bab9dfa55
http://arxiv.org/abs/2106.13493
http://arxiv.org/abs/2106.13493
Autor:
Tang, Zhenyu, Manocha, Dinesh
We propose a novel method for generating scene-aware training data for far-field automatic speech recognition. We use a deep learning-based estimator to non-intrusively compute the sub-band reverberation time of an environment from its speech samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a4e47c5aa3321e780d7ffc5789f28bcc
http://arxiv.org/abs/2104.10757
http://arxiv.org/abs/2104.10757
We present a method for improving the quality of synthetic room impulse responses for far-field speech recognition. We bridge the gap between the fidelity of synthetic room impulse responses (RIRs) and the real room impulse responses using our novel,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad5d96b6a1841b2b633ecccdabec5584
We present a novel approach that improves the performance of reverberant speech separation. Our approach is based on an accurate geometric acoustic simulator (GAS) which generates realistic room impulse responses (RIRs) by modeling both specular and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12abc7c51e3cc9379012ae49aef5e816