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Dual-channel eKF-RTF framework for speech enhancement with DNN-based speech presence estimation
dc.contributor.author | Martín Doñas, Juan M. | |
dc.contributor.author | Peinado Herreros, Antonio Miguel | |
dc.contributor.author | López Espejo, Iván | |
dc.contributor.author | Gómez García, Ángel Manuel | |
dc.date.accessioned | 2023-03-14T08:07:47Z | |
dc.date.available | 2023-03-14T08:07:47Z | |
dc.date.issued | 2021-03 | |
dc.identifier.uri | https://hdl.handle.net/10481/80569 | |
dc.description.abstract | This paper presents a dual-channel speech enhance- ment framework that effectively integrates deep neural net- work (DNN) mask estimators. Our framework follows a beamforming-plus-postfiltering approach intended for noise reduction on dual-microphone smartphones. An extended Kalman filter is used for the estimation of the relative acous- tic channel between microphones, while the noise estimation is performed using a speech presence probability estimator. We propose the use of a DNN estimator to improve the prediction of the speech presence probabilities without making any assump- tion about the statistics of the signals. We evaluate and compare different dual-channel features to improve the accuracy of this estimator, including the power and phase difference between the speech signals at the two microphones. The proposed in- tegrated scheme is evaluated in different reverberant and noisy environments when the smartphone is used in both close- and far-talk positions. The experimental results show that our ap- proach achieves significant improvements in terms of speech quality, intelligibility, and distortion when compared to other approaches based only on statistical signal processing. | es_ES |
dc.description.sponsorship | Spanish Ministry of Science and Innovation Project No. PID2019-104206GB- I00/AEI/10.13039/501100011033 | es_ES |
dc.description.sponsorship | Spanish Ministry of Uni- versities through the National Program FPU (grant reference FPU15/04161) | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Proceedings of IBERSPEECH 2021 | es_ES |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Dual-microphone smartphone | es_ES |
dc.subject | Beamforming | es_ES |
dc.subject | Extended Kalman filter | es_ES |
dc.subject | Speech presence probability | es_ES |
dc.subject | Deep Neural Network | es_ES |
dc.title | Dual-channel eKF-RTF framework for speech enhancement with DNN-based speech presence estimation | es_ES |
dc.type | conference output | es_ES |
dc.rights.accessRights | open access | es_ES |
dc.identifier.doi | 10.21437/IberSPEECH.2021-7 | |
dc.type.hasVersion | SMUR | es_ES |