Speech Enhancement Tutorial Home

Contents

Introduction

1) Noise Types

2) Aims

Evaluation

1) Introduction

2) Speech Intelligibility

a) Subjective Measures

i) Phonetic Tests

ii) Word Intelligibility

iii) Sentece Intelligibility

b) Objective Measures

2) Speech Quality

a) Subjective measures

ii) Preference Tests

b) Objective Measures

i) Intrusive Methods

ii) Non-Intrusive Methods

Enhancement

1) Introduction

2) Frame Processing

3) Spectral Subtraction

4) Minimum Mean Square Estimators (MMSE)

5) Super Gaussian Estimates

6) Subspace Methods

7) Adaptive Filtering

9) Harmonic & Impulsive Noise

10) Missing Feature Extraction

11) Restoring Clipped Signals

12) Bandwidth Expansion

13) Reverberation

a) Speech Model Enhancement

b) System Identification

Noise Estimation

1) Introduction

2) Noise Models

a) Stationary Noise Model

b) Two Component Model

c) Hidden Markov Model

3) Minimum Statistics

4) Voice Activity Detectors

a) Energy Histogram

b) Magnitude Histogram

c) Energy Waveform

e) Soft Decision VAD

5) Speech Model

Home

Welcome to the online Speech Enhancement Tutorial. This tutorial is intended to give an overview of the Speech Enahancement area of Speech Processing within the larger field of Digital Signal Processing.

This tutorial is divided into four parts:

Introduction - here we will introduce the topic of Speech Enhancement, together with its aims and diffrenet noise types.

Evaluation Methods - here we deal with the key issues relating to the measurement of the improvement in the quality of speech.

Speech Enhancement - differenent appraches for speech enhancement are discussed here.

Noise Estimation - the different techniques for noise estimation are presented in this final section.

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