Chapter: Digital Signal Processing - Applications of DSP

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Speech signal processing

The topic of speech signal processing can be loosely defined as the manipulation of sampled speech signals by a digital processor to obtain a new signal with some desired properties.

Speech signal processing:

 

The topic of speech signal processing can be loosely defined as the manipulation of sampled speech signals by a digital processor to obtain a new signal with some desired properties.

Speech signal processing is a diverse field that relies on knowledge of language at the levels of Signal processing

Acoustics (P¥)

Phonetics ( ^ ^ ^ ) Language-independent

Phonology ( ^ ^ )

Morphology ( i ^ ^ ^ )

Syntax ( ^ , £ ) Language-dependent

Semantics (\%X¥) Pragmatics ( i f , f f l ^ )

 

 7 layers for describing speech From Speech to Speech Signal, in terms of Digital Signal Processing

 



 

It is based on the fact that 

- Most of energy between 20 Hz to about 7KHz , 

- Human ear sensitive to energy between 50 Hz and 4KHz 

© In terms of acoustic or perceptual, above features are considered. 

© From Speech to Speech Signal, in terms of Phonetics (Speech production), the digital model of Speech Signal will be discussed in Chapter 2. 

© Motivation of converting speech to digital signals: 



Speech coding, A PC and SBC fine


Adaptive predictive coding (APC) is a technique used for speech coding, that is data compression of spccch signals APC assumes that the input  speech signal is repetitive with a period significantly longer than the average frequency content.  Two predictors arc used in APC.

The high frequency components (up to 4 kHz) are estimated using a 'spectral’ or 'formant’ prcdictor and the low frequency components (50-200 Hz) by a ‘pitch’ or ‘fine structure’ prcdictor (see figure 7.4). The spcctral estimator may he of order 1- 4 and the pitch estimator about order 10. The low-frequency components of the spccch signal are due to the movement of the tongue, chin and spectral envelope, formants


The high-frequency components originate from the vocal chords and the noise-like sounds (like in ‘s’) produced in the front of the mouth.

 

The output signal y(n)together with the predictor parameters, obtained adaptively in the encoder, are transmitted to the decoder, where the spcech signal is reconstructed. The decoder has the same structure as the encoder but the predictors arc not adaptive and arc invoked in the reverse order. The prediction parameters are adapted for blocks of data corresponding to for instance 20 ms time periods.

 

A PC' is used for coding spcech at 9.6 and 16 kbits/s. The algorithm works well in noisy environments, but unfortunately the quality of the processed speech is not as good as for other methods like CELP described on next page.

 

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