About this Research Topic
The advent of deep learning in audio processing created a significant additional boost in performance of speech and audio processing techniques. Nowadays, this research field experiences an interesting transition, where deep learning-based, as well as traditional statistical model-based techniques, are welcome, show different properties and can be used separately, in a hybrid way, or should be carefully evaluated against each other. This Research Topic will comprise advances of state-of-the-art and novel audio and speech processing algorithms.
In this Research Topic, we are seeking submissions in the following areas, but not limited to:
• Single- and multi-channel speech enhancement
• Speech and sound source separation
• Deep learning for speech enhancement
• Intelligibility enhancement for normal hearing, hearing impaired, or machine listeners
• Sound source localization and tracking
• Speech activity detection
• Detection or classification of speech or signal-related parameters like reverberation time, signal-to-noise ratio, etc.
Topic editor Sebastian Braun is employed by Microsoft. All other Topic Editors declare no competing interests with regards to the Research Topic subject.
Keywords: speech enhancement, noise reduction, dereverberation, echo cancellation, beamforming, speech separation
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.