Abstract
With the continuous development of artiticial intelligence techniques, many new solutions have emerged for acoustic echo cancellation. Acoustic echo cancellation, a key problem in contemporary audio communication, is gradually being replaced by traditional filter algorithms with deep learning-based approaches. In this paper, traditional filter algorithms and neural network models based on deep learning theory are used to solve the task of acoustic echo cancellation respectively. Comparative experiments are performed on popular models using the dataset from the 2021 Acoustic Echo Cancellation Challenge. The experimental results demonstrate the good results and importance of neural networks in acoustic echo cancellation tasks.
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