Speech Enhancement Using Pitch Detection Approach For Noisy Environment
This work addresses speech enhancement for real-world applications like mathematical symbol recognition in schools, but it appears incremental as it builds on existing pre-processing techniques without claiming major breakthroughs.
The paper tackles the problem of speech recognition degradation in noisy environments by proposing a pitch detection approach to reinforce speech signals rather than removing noise, and subjective evaluation shows improved perceptual quality in various noisy conditions.
Acoustical mismatch among training and testing phases degrades outstandingly speech recognition results. This problem has limited the development of real-world nonspecific applications, as testing conditions are highly variant or even unpredictable during the training process. Therefore the background noise has to be removed from the noisy speech signal to increase the signal intelligibility and to reduce the listener fatigue. Enhancement techniques applied, as pre-processing stages; to the systems remarkably improve recognition results. In this paper, a novel approach is used to enhance the perceived quality of the speech signal when the additive noise cannot be directly controlled. Instead of controlling the background noise, we propose to reinforce the speech signal so that it can be heard more clearly in noisy environments. The subjective evaluation shows that the proposed method improves perceptual quality of speech in various noisy environments. As in some cases speaking may be more convenient than typing, even for rapid typists: many mathematical symbols are missing from the keyboard but can be easily spoken and recognized. Therefore, the proposed system can be used in an application designed for mathematical symbol recognition (especially symbols not available on the keyboard) in schools.