The CITISEN provides three functions: speech enhancement (SE), model adaptation (MA), and background noise conversion (BNC), allowing CITISEN to be used as a platform for utilizing and evaluating SE models and flexibly extend the models to address various noise environments and users.
no code implementations • 18 Jun 2020 • Szu-Wei Fu, Chien-Feng Liao, Tsun-An Hsieh, Kuo-Hsuan Hung, Syu-Siang Wang, Cheng Yu, Heng-Cheng Kuo, Ryandhimas E. Zezario, You-Jin Li, Shang-Yi Chuang, Yen-Ju Lu, Yu Tsao
The Transformer architecture has demonstrated a superior ability compared to recurrent neural networks in many different natural language processing applications.
For speech-related applications in IoT environments, identifying effective methods to handle interference noises and compress the amount of data in transmissions is essential to achieve high-quality services.
We also propose an extended version of SDFCN, called the residual SDFCN (termed rSDFCN).