A pitch based noise estimation technique for robust speech recognition with Missing Data

This paper presents a noise estimation technique based on knowledge of pitch information for robust speech recognition. In the first stage the noise is estimated by means of extrapolating the noise from frames where speech is believed to be absent. These frames are detected with a proposed pitch based VAD (Voice Activity Detector). In the second stage the noise estimation is revised in voiced frames using harmonic tunnelling technique. The tunnelling noise estimation is used at high SNRs as an upper bound of the noise rather than a suitable estimation. A spectrogram MD (Missing Data) recognition system is chosen to evaluate the proposed noise estimation. The proposed system is compared in Aurora-2 with other similar techniques like cepstral SS (Spectral Subtraction).