Abstract
The Fractional Fourier Transform (FrFT) can be interpreted as a rotation in the time-frequency plane with an angle α. It describes the speech signal characteristics as the signal changes from time to frequency domain. However, to locate the fractional Fourier domain frequency contents and multicomponent analysis of nonlinear chirp like signals such as speech the Short-Time FrFT (SFrFT) can provide an improved time-frequency resolution. By representing the time and fractional frequency domain information simultaneously, the SFrFT can filter out cross terms and distortion in a signal adequately for better signal enhancement. The method has experienced with better Signal to Noise Ratio (SNR) and Perceptual Evaluation of Speech Quality (PESQ) under different noisy conditions as compared to the conventional FrFT in our results.
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Ram, R., Palo, H.K., Mohanty, M.N. (2019). Fractional Segmental Transform for Speech Enhancement. In: Bhaskar, M., Dash, S., Das, S., Panigrahi, B. (eds) International Conference on Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 846. Springer, Singapore. https://doi.org/10.1007/978-981-13-2182-5_14
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DOI: https://doi.org/10.1007/978-981-13-2182-5_14
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