By Ian McLoughlin
Utilized Speech and Audio Processing is a MATLAB-based, one-stop source that blends speech and listening to learn in describing the most important strategies of speech and audio processing. This essentially orientated textual content offers MATLAB examples all through to demonstrate the suggestions mentioned and to offer the reader hands-on event with very important strategies. Chapters on uncomplicated audio processing and the features of speech and listening to lay the rules of speech sign processing, that are outfitted upon in next sections explaining audio dealing with, coding, compression, and research strategies. the ultimate bankruptcy explores a couple of complex subject matters that use those strategies, together with psychoacoustic modelling, an issue which underpins MP3 and similar audio codecs. With its hands-on nature and various MATLAB examples, this e-book is perfect for graduate scholars and practitioners operating with speech or audio platforms.
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Additional info for Applied Speech and Audio Processing: With Matlab Examples
3 Speech understanding Up to now, this chapter has investigated the production of speech and the characteristics of the produced speech. Ignoring aspects of whichever communications mechanism has been used, this section will now consider some of the non-auditory factors involved in the understanding of speech by humans. That is, the nature of speech structure and how that relates to understanding, rather than the nature of human hearing and perception of speech (which will be covered in Chapter 4).
For each analysis window we could perform an FFT, and look for peaks in the spectrum. However if we analysed longer duration windows, we may end up performing an FFT that spans across two notes, and be unable to determine which is either note. At very least we would have a confused ‘picture’ of the sound being analysed – just as the example FFT in the Infobox did not reveal the full detail of the sound being analysed. More importantly, the theory that gives rise to the FFT assumes that the frequency components of the signal are unchanging across the analysis window of interest.
The frames cannot simply be concatenated because there would then be twice as many samples, and adding them together won’t work either. 5 illustrates another problem if frames have been split, processed and then rejoined: there is a discontinuity between neighbouring frames. Something like this is very easily audible to the ear which perceives it as a clicking sound. In fact it turns out that almost any type of non-trivial processing will result in such discontinuities. 2 Windowing The work-around for many of the segmentation and overlap problems is windowing prior to reassembly.