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Found 4 papers, 1 papers with code
Multichannel Speech Enhancement by Raw Waveform-mapping using Fully Convolutional Networks
We also propose an extended version of SDFCN, called the residual SDFCN (termed rSDFCN).
MIMO Speech Compression and Enhancement Based on Convolutional Denoising Autoencoder
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.
Boosting Objective Scores of a Speech Enhancement Model by MetricGAN Post-processing
The Transformer architecture has demonstrated a superior ability compared to recurrent neural networks in many different natural language processing applications.
CITISEN: A Deep Learning-Based Speech Signal-Processing Mobile Application
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.
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