MFCC based noise reduction in ASR using Kalman filtering
Anuradha P Nair, Shoba Krishnan, Zia Saquib · 2016
Speech enhancement using Kalman filter is an extensively researched area. The vast majority of work done in this area uses linear predictive coding (LPC) for modeling speech signal. A few important studies have revealed the superiority of Mel Frequency Cepstral Coefficients (MFCC) over LPC for speech recognition. With this paper, the shortcomings of speech enhancement using LPC with Kalman filters have been elaborated and MFCC, a much more favored technique is used along with Kalman filter to ascertain proficient parameters from a noisy signal, which can be used for Automatic speech recognition (ASR).