By Chin-hue Lee, Haizhou Li, Lin-shan Lee, Ren-hua Wang, Qiang Huo
After many years of study job, chinese language spoken language processing (CSLP) has complex significantly either in useful know-how and theoretical discovery. during this publication, the editors offer either an creation to the sector in addition to targeted learn issues of their ideas in quite a few parts of CSLP. The contributions characterize pioneering efforts starting from CSLP rules to applied sciences and purposes, with every one bankruptcy encapsulating a unmarried challenge and its ideas.
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Extra info for Advances in Chinese Spoken Language Processing
Most channel effects, except in severe fading conditions) are thus eliminated by the highpass filtering. The lowpass cutoff is more gradual, which smoothes parameters over about 40 ms, thus preserving most phonetic events, while suppressing noise. 2. Mel-Frequency Cepstral Analysis Another popular speech analysis method that jointly exploits speech production and perception mechanisms is Mel-frequency cepstral analysis. The results of this analysis are often called Mel-frequency cepstral coefficients (MFCCs).
1. Introduction to LPC The most prominent method in speech analysis, linear predictive coding (LPC), has been directly motivated by our understanding of the physical properties of the human speech production system. LPC analysis has had a successful history for more than 30 years. The term "linear prediction" refers to the mechanism of using a linear combination of the past time-domain samples to approximate or to "predict" the current time-domain sample, using a compact set of LPC coefficients.
The simplest window has a rectangular shape, which gives equal weight to all samples of the speech signal and limits the analysis range to width of the window. A common is the Hamming window, which is a raised cosine pulse, or the quite similar Hanning window. Tapering the edges of the window allows its periodic shifting (at the update frame rate) along without having large effects on the resulting speech parameters due to pitch period boundaries. 2. Short-Time Average Zero-Crossing Rate Speech analysis that attempts to estimate spectral features usually requires a Fourier transform.