Build A Module for Improvement Real Time Speech enhancement using Long Short-term Memory Approach

An essential customer experience is required for all businesses today, and customer support as a service brings the right people and processes together. When designing a system for in the context of audio communication for transmission purposes, noise influences must be carefully considered. Improving the quality of phone calls for a smart virtual call center is essential for more effective customer care. This paper proposed a module for improving real-time speech enhancement of phone calls using Long short-term memory (LSTM), an artificial neural network used in the fields of artificial intelligence and deep learning. LSTMs are designed to revoke the long-term dependency issue, remembering information for long periods is generally their default way of behaving. The data set using for this approach is both in English and Vietnamese, the results also improve with evaluation metrics such as PESQ, SI-SDR, STOI.