https://scholars.lib.ntu.edu.tw/handle/123456789/640005
標題: | LC4SV: A Denoising Framework Learning to Compensate for Unseen Speaker Verification Models | 作者: | Lee, Chi Chang Chen, Hong Wei CHU-SONG CHEN Wang, Hsin Min TSUNG-TE LIU Tsao, Yu |
關鍵字: | reinforcement learning | speaker identification | speaker verification | speech enhancement | 公開日期: | 1-一月-2023 | 來源出版物: | 2023 IEEE Automatic Speech Recognition and Understanding Workshop, ASRU 2023 | 摘要: | The performance of speaker verification (SV) models may drop dramatically in noisy environments. A speech enhancement (SE) module can be used as a front-end strategy. However, existing SE methods may fail to bring performance improvements to downstream SV systems due to artifacts in the predicted signals of SE models. To compensate for artifacts, we propose a generic denoising framework named LC4SV, which can serve as a pre-processor for various unknown downstream SV models. In LC4SV, we employ a learning-based interpolation agent to automatically generate the appropriate coefficients between the enhanced signal and its noisy input to improve SV performance in noisy environments. Our experimental results demonstrate that LC4SV consistently improves the performance of various unseen SV systems. To the best of our knowledge, this work is the first attempt to develop a learning-based interpolation scheme aiming at improving SV performance in noisy environments. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/640005 | ISBN: | 9798350306897 | DOI: | 10.1109/ASRU57964.2023.10389793 |
顯示於: | 資訊工程學系 |
在 IR 系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。