Short-time phase spectrum in speech processing: A review and some experimental results

Incorporating information from the short-time phase spectrum into a feature set for automatic speech recognition (ASR) may possibly serve to improve recognition accuracy. Currently, however, it is common practice to discard this information in favour of features that are derived purely from the short-time magnitude spectrum. There are two reasons for this: (1) the results of some well-known human listening experiments have indicated that the short-time phase spectrum conveys a negligible amount of intelligibility at the small window durations of 20–40 ms used for ASR spectral analysis, and (2) using the short-time phase spectrum directly for ASR has proven difficult from a signal processing viewpoint, due to phase-wrapping and other problems. In this article, we explore the possibility of using short-time phase spectrum information for ASR by considering the two points mentioned above. To address the first point, we review the results of our own set of human listening experiments....

• Type: Journal
• Year: 2007
• Where: DSP
• Authors: Leigh D. Alsteris, Kuldip K. Paliwal
• Keywords: DSP 2007, DSP 2010, Short-time Magnitude Spectrum, Short-time Phase Spectrum, Small Window Durations