Filtering of spectral parameters for speech recognition

The time sequences of speech parameters resulting from current short-time spectral estimators show a tradeoff between estimation error variance and time and frequency resolution. In this paper, we apply frequency analysis and linear filtering to these sequences to gain insights into their limitations and to provide an interpretation framework for several parameter processing techniques proposed in the past. Particularly, the observation of their long-term spectrum reveals the importance of band equalization for improving discrimination in speech recognition. Based on that, we propose a method of filtering the sequences that includes an explicit equalization and incorporates a bandwidth parameter. By using Slepian sequences in the design of the filters, good results were obtained in our preliminary word recognition tests.Peer Reviewe