Speech coding

About: Speech coding is a research topic. Over the lifetime, 14245 publications have been published within this topic receiving 271964 citations.

Interactive speech recognition with varying responses for time of day and environmental conditions

Abstract: The invention improves recognition rates by providing an interactive speech recognition device that performs recognition by taking situational and environmental changes into consideration, thus enabling interactions that correspond to situational and environmental changes. The invention comprises a speech analysis unit that creates a speech data pattern corresponding to the input speech; a timing circuit for generating time data, for example, as variable data; a coefficient setting unit receiving the time data from the timing circuit and generating weighting coefficients that change over time, in correspondence to the content of each recognition target speech; a speech recognition unit that receives the speech data pattern of the input speech from the speech analysis unit, and that at the same time obtains a weighting coefficient in effect for a pre-registered recognition target speech at the time from the coefficient setting unit, that computes final recognition data by multiplying the recognition data corresponding to each recognition target speech by its corresponding weighting coefficient, and that recognizes the input speech based on the computed final recognition result; a speech synthesis unit for outputting speech synthesis data based on the recognition data that takes the weighting coefficient into consideration; and a drive control unit for transmitting the output from the speech synthesis unit to the outside.

Method and apparatus for hybrid coding of speech at 4KBPS having phase alignment between mode-switched frames

Abstract: A method and apparatus for encoding speech for communication to a decoder for reproduction of the speech where the speech signal is classified into steady state voiced (harmonic), stationary unvoiced, and “transitory” or “transition” speech, and a particular type of coding scheme is used for each class. Harmonic coding is used for steady state voiced speech, “noise-like” coding is used for stationary unvoiced speech, and a special coding mode is used for transition speech, designed to capture the location, the structure, and the strength of the local time events that characterize the transition portions of the speech. The compression schemes can be applied to the speech signal or to the LP residual signal.

Digital audio compression

Abstract: Compared to most digital data types, with the exception of digital video, the data rates associated with uncompressed digital audio are substantial. Digital audio compression enables more efficient storage and transmission of audio data. The many forms of audio compression techniques offer a range of encoder and decoder complexity, compressed audio quality, and differing amounts of data compression. The -law transformation and ADPCM coder are simple approaches with low-complexity, low-compression, and medium audio quality algorithms. The MPEG/audio standard is a highcomplexity, high-compression, and high audio quality algorithm. These techniques apply to general audio signals and are not specifically tuned for speech signals.

System for tdma mobile-to-mobile vselp codec bypass

Abstract: In a TDMA mobile-to-mobile connection, the end-to-end audio signal quality as well as system performance can be improved by providing digital signal processors the capability to automatically switch configuration such that each digital signal processor in a mobile-to-mobile communication connection can automatically identify a TDMA mobile-to-mobile connection and bypass the speech encoding and decoding processes within the digital signal processors. The two digital signal processors are virtually connected at the channel codecs.

Multimedia Signal Processing: Theory and Applications in Speech, Music and Communications

Abstract: Preface Acknowledgement Symbols Abbreviations Part I Basic Digital Signal Processing 1 Introduction 11 Signals and Information 12 Signal Processing Methods 13 Applications of Digital Signal Processing 14 Summary 2 Fourier Analysis and Synthesis 21 Introduction 22 Fourier Series: Representation of Periodic Signals 23 Fourier Transform: Representation of Nonperiodic Signals 24 Discrete Fourier Transform 25 Short-Time Fourier Transform 26 Fast Fourier Transform (FFT) 27 2-D Discrete Fourier Transform (2-D DFT) 28 Discrete Cosine Transform (DCT) 29 Some Applications of the Fourier Transform 210 Summary 3 z-Transform 31 Introduction 32 Derivation of the z-Transform 33 The z-Plane and the Unit Circle 34 Properties of z-Transform 35 z-Transfer Function, Poles (Resonance) and Zeros (Anti-resonance) 36 z-Transform of Analysis of Exponential Transient Signals 37 Inverse z-Transform 38 Summary 4 Digital Filters 41 Introduction 42 Linear Time-Invariant Digital Filters 43 Recursive and Non-Recursive Filters 44 Filtering Operation: Sum of Vector Products, A Comparison of Convolution and Correlation 45 Filter Structures: Direct, Cascade and Parallel Forms 46 Linear Phase FIR Filters 47 Design of Digital FIR Filter-banks 48 Quadrature Mirror Sub-band Filters 49 Design of Infinite Impulse Response (IIR) Filters by Pole-zero Placements 410 Issues in the Design and Implementation of a Digital Filter 411 Summary 5 Sampling and Quantisation 51 Introduction 52 Sampling a Continuous-Time Signal 53 Quantisation 54 Sampling Rate Conversion: Interpolation and Decimation 55 Summary Part II Model-Based Signal Processing 6 Information Theory and Probability Models 61 Introduction: Probability and Information Models 62 Random Processes 63 Probability Models of Random Signals 64 Information Models 65 Stationary and Non-Stationary Random Processes 66 Statistics (Expected Values) of a Random Process 67 Some Useful Practical Classes of Random Processes 68 Transformation of a Random Process 69 Search Engines: Citation Ranking 610 Summary 7 Bayesian Inference 71 Bayesian Estimation Theory: Basic Definitions 72 Bayesian Estimation 73 Expectation Maximisation Method 74 Cramer-Rao Bound on the Minimum Estimator Variance 75 Design of Gaussian Mixture Models (GMM) 76 Bayesian Classification 77 Modelling the Space of a Random Process 78 Summary 8 Least Square Error, Wiener-Kolmogorov Filters 81 Least Square Error Estimation: Wiener-Kolmogorov Filter 82 Block-Data Formulation of the Wiener Filter 83 Interpretation of Wiener Filter as Projection in Vector Space 84 Analysis of the Least Mean Square Error Signal 85 Formulation of Wiener Filters in the Frequency Domain 86 Some Applications of Wiener Filters 87 Implementation of Wiener Filters 88 Summary 9 Adaptive Filters: Kalman, RLS, LMS 91 Introduction 92 State-Space Kalman Filters 93 Sample Adaptive Filters 94 Recursive Least Square (RLS) Adaptive Filters 95 The Steepest-Descent Method 96 LMS Filter 97 Summary 10 Linear Prediction Models 101 Linear Prediction Coding 102 Forward, Backward and Lattice Predictors 103 Short-Term and Long-Term Predictors 104 MAP Estimation of Predictor Coefficients 105 Formant-Tracking LP Models 106 Sub-Band Linear Prediction Model 107 Signal Restoration Using Linear Prediction Models 108 Summary 11 Hidden Markov Models 111 Statistical Models for Non-Stationary Processes 112 Hidden Markov Models 113 Training Hidden Markov Models 114 Decoding Signals Using Hidden Markov Models 115 HMM in DNA and Protein Sequences 116 HMMs for Modelling Speech and Noise 117 Summary 12 Eigenvector Analysis, Principal Component Analysis and Independent Component Analysis 121 Introduction - Linear Systems and Eigenanalysis 122 Eigenvectors and Eigenvalues 123 Principal Component Analysis (PCA) 124 Independent Component Analysis 125 Summary Part III Applications of Digital Signal Processing to Speech, Music and Telecommunications 13 Music Signal Processing and Auditory Perception 131 Introduction 132 Musical Notes, Intervals and Scales 133 Musical Instruments 134 Review of Basic Physics of Sounds 135 Music Signal Features and Models 136 Anatomy of the Ear and the Hearing Process 137 Psychoacoustics of Hearing 138 Music Coding (Compression) 139 High Quality Audio Coding: MPEG Audio Layer-3 (MP3) 1310 Stereo Music Coding 1311 Summary 14 Speech Processing 141 Speech Communication 142 Acoustic Theory of Speech: The Source-filter Model 143 Speech Models and Features 144 Linear Prediction Models of Speech 145 Harmonic Plus Noise Model of Speech 146 Fundamental Frequency (Pitch) Information 147 Speech Coding 148 Speech Recognition 149 Summary 15 Speech Enhancement 151 Introduction 152 Single-Input Speech Enhancement Methods 153 Speech Bandwidth Extension - Spectral Extrapolation 154 Interpolation of Lost Speech Segments - Packet Loss Concealment 155 Multi-Input Speech Enhancement Methods 156 Speech Distortion Measurements 157 Summary 16 Echo Cancellation 161 Introduction: Acoustic and Hybrid Echo 162 Telephone Line Hybrid Echo 163 Hybrid (Telephone Line) Echo Suppression 164 Adaptive Echo Cancellation 165 Acoustic Echo 166 Sub-Band Acoustic Echo Cancellation 167 Echo Cancellation with Linear Prediction Pre-whitening 168 Multi-Input Multi-Output Echo Cancellation 169 Summary 17 Channel Equalisation and Blind Deconvolution 171 Introduction 172 Blind Equalisation Using Channel Input Power Spectrum 173 Equalisation Based on Linear Prediction Models 174 Bayesian Blind Deconvolution and Equalisation 175 Blind Equalisation for Digital Communication Channels 176 Equalisation Based on Higher-Order Statistics 177 Summary 18 Signal Processing in Mobile Communication 181 Introduction to Cellular Communication 182 Communication Signal Processing in Mobile Systems 183 Capacity, Noise, and Spectral Efficiency 184 Multi-path and Fading in Mobile Communication 185 Smart Antennas - Space-Time Signal Processing 186 Summary Index