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Contents
Speech Analysis
Tony Robinson
Lent Term 1998
Contents
Introduction
What is Speech Analysis?
So what is an acoustic vector?
Why Speech Analysis?
The problems of speech analysis
Standard references for this course
Background
Sampling theory
Sampling frequency
Sampling resolution
Linear filters
Finite Impulse Response filters
Infinite Impulse Response filters
The source filter model of speech
Filter bank Analysis
Spectrograms
Non-linear frequency scales
Short-Term Fourier Analysis
Properties of the DFT
Linearity
Time Shift
Frequency Shift
Convolution
Real valued input
Windowing
The short-term Fourier transform
Zero padding
Fast Fourier transforms
Practical application of the short-term Fourier transform
Overlap and add for linear filtering
Example: Spectral subtraction
Cepstral analysis
Homomorphic filtering
Mel scaled analysis
The Autocorrelation from the FFT
Z
transforms
Linear Prediction analysis
Motivation from lossless tubes
Parameter estimation
The autocorrelation method
The covariance method
Pre-emphasis
The LP spectrum
Gain computation
The lattice filter implementation
The Itakura distance measure
The LP cepstrum
Log area ratios
The roots of the predictor polynomial
Line spectral pairs
Perceptual Linear Prediction
Spectral Analysis
Critical-band spectral resolution
Equal loudness preemphasis
Intensity-loudness power law
Autoregressive modelling
Discussion
Formant analysis
Motivation
Obtaining candidate values
Peak picking on the smoothed spectrum
Peak picking on the LP spectrum
Factoring for the LP roots
Fitting ``bumps''
Combining candidates
Voicing analysis
Pitch synchronous analysis
Zero-crossing points
Peak in the autocorrelation function
Peak in the autocorrelation of the LP residual
The average magnitude difference function
Peak in the cepstrum
Combining candidates
Degree of voicing
Voicing determination
Usage
Speech coding
Waveform coders
Pulse Code Modulation (PCM)
Differential Pulse Code Modulation (DPCM)
Adaptive Differential Code Modulation (ADPCM)
Example: lossless waveform coding
Sub-band coders
Linear prediction vocoders
Parameter updating
Example: LPC10
Formant coders
Multi-pulse coders
Backwards adaptation
CELP coders
Audio demonstration
References
About this document ...
Speech Vision Robotics group
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Tony Robinson