Effect of filter bandwidth and spectral sampling rate of analysis filterbank on automatic phoneme recognition

In this study we investigate the effect of filter bandwidth and spectral sampling rate of analysis filterbank for speech recognition. Two experiments are conducted to evaluate the performance of an automatic phoneme recognition system on clean speech and speech in noise as the filter bandwidth increases from 0.5 to 3.5 ERB and the spectral resolution changes from 1, 1.5, 2, 3, 4, to 6 samples per Bark. Results indicate that the optimum filter bandwidth varies for different speech sounds at different frequency ranges. A spectral sampling of 4 filters per Bark with the filter bandwidth being ≈ 1 ERB produces the best performance on average.