Application of Deep Learning in Speech Enhancement Technology
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".
Deadline for manuscript submissions: 30 May 2025 | Viewed by 192
Special Issue Editor
Interests: signal processing; machine learning; robot perception
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Speech enhancement aims to improve the quality of speech degraded by environmental noise with signal-processing techniques and is used in many applications such as voice communication, hearing aids, speech recognition, and human–robot interaction. In recent years, the research in speech enhancement has advanced significantly with deep learning and artificial intelligence techniques. When sufficient training data are available, deep neural networks can learn to predict speech from the noisy signal, achieving promising results in non-stationary and highly noisy acoustic environments. For this reason, deep learning-based speech enhancement has been investigated intensively and is becoming a hot spot in the field of speech processing. A number of methods have been developed with the aim of solving speech enhancement problems in extremely challenging environments, developing new deep architectures, increasing the generality and explainability of the deep model, incorporating deep learning into multi-channel signal processing, and multi-modal speech enhancement. This Special Issue aims to accelerate the research progress by reporting the latest theoretical and practical advances applying deep learning to speech enhancement, discussing emerging problems, creative solutions, and novel insights in the field. This Special Issue will mainly focus on (but is not limited to) the following deep learning-related topics:
- Single-channel speech enhancement;
- Multi-channel speech enhancement;
- Multi-modal speech enhancement;
- Explainable speech enhancement;
- Novel applications of speech enhancement.
Dr. Lin Wang
Guest Editor
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Keywords
- deep learning
- explainable AI
- microphone array
- multi-modal speech processing
- noise reduction
- speech enhancement
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