Chapter 20 Speech Encoding by Parameters 20.1 Linear Predictive Coding (LPC) 20.2 Linear Predictive Vocoder 20.3 Code Excited Linear Prediction (CELP)

Slides:



Advertisements
Similar presentations
Speech Coding Workshop 2000 Jean-Marc Valin, Roch Lefebvre 1 IEEE Speech Coding Workshop Sept 17–20, 2000 Lake Lawn Resort Delavan, WI Jean-Marc Valin,
Advertisements

ECE 8443 – Pattern Recognition ECE 8423 – Adaptive Signal Processing Objectives: The Linear Prediction Model The Autocorrelation Method Levinson and Durbin.
Speech & Audio Coding TSBK01 Image Coding and Data Compression Lecture 11, 2003 Jörgen Ahlberg.
Liner Predictive Pitch Synchronization Voiced speech detection, analysis and synthesis Jim Bryan Florida Institute of Technology ECE5525 Final Project.
Page 0 of 34 MBE Vocoder. Page 1 of 34 Outline Introduction to vocoders MBE vocoder –MBE Parameters –Parameter estimation –Analysis and synthesis algorithm.
A 12-WEEK PROJECT IN Speech Coding and Recognition by Fu-Tien Hsiao and Vedrana Andersen.
Itay Ben-Lulu & Uri Goldfeld Instructor : Dr. Yizhar Lavner Spring /9/2004.
Speech in Multimedia Hao Jiang Computer Science Department Boston College Oct. 9, 2007.
Speech Coding Nicola Orio Dipartimento di Ingegneria dell’Informazione IV Scuola estiva AISV, 8-12 settembre 2008.
1 Speech Parametrisation Compact encoding of information in speech Accentuates important info –Attempts to eliminate irrelevant information Accentuates.
Overview of Adaptive Multi-Rate Narrow Band (AMR-NB) Speech Codec
Pole Zero Speech Models Speech is nonstationary. It can approximately be considered stationary over short intervals (20-40 ms). Over thisinterval the source.
EE2F1 Speech & Audio Technology Sept. 26, 2002 SLIDE 1 THE UNIVERSITY OF BIRMINGHAM ELECTRONIC, ELECTRICAL & COMPUTER ENGINEERING Digital Systems & Vision.
System Microphone Keyboard Output. Cross Synthesis: Two Implementations.
Communications & Multimedia Signal Processing Formant Tracking LP with Harmonic Plus Noise Model of Excitation for Speech Enhancement Qin Yan Communication.
Voice Transformation Project by: Asaf Rubin Michael Katz Under the guidance of: Dr. Izhar Levner.
Warped Linear Prediction Concept: Warp the spectrum to emulate human perception; then perform linear prediction on the result Approaches to warp the spectrum:
1 Audio Compression Multimedia Systems (Module 4 Lesson 4) Summary: r Simple Audio Compression: m Lossy: Prediction based r Psychoacoustic Model r MPEG.
DSP C5000 Chapter 23 Mobile Communication Speech Coders Copyright © 2003 Texas Instruments. All rights reserved.
Speech Coding Using LPC. What is Speech Coding  Speech coding is the procedure of transforming speech signal into more compact form for Transmission.
Page 0 of 23 MELP Vocoders Nima Moghadam SN#: Saeed Nari SN#: Supervisor Dr. Saameti April 2005 Sharif University of Technology.
Chapter 16 Speech Synthesis Algorithms 16.1 Synthesis based on LPC 16.2 Synthesis based on formants 16.3 Synthesis based on homomorphic processing 16.4.
Comparing Audio Signals Phase misalignment Deeper peaks and valleys Pitch misalignment Energy misalignment Embedded noise Length of vowels Phoneme variance.
Speech Coding Submitted To: Dr. Mohab Mangoud Submitted By: Nidal Ismail.
Concepts of Multimedia Processing and Transmission IT 481, Lecture #4 Dennis McCaughey, Ph.D. 25 September, 2006.
SPEECH CODING Maryam Zebarjad Alessandro Chiumento.
1 Linear Prediction. 2 Linear Prediction (Introduction) : The object of linear prediction is to estimate the output sequence from a linear combination.
1 PATTERN COMPARISON TECHNIQUES Test Pattern:Reference Pattern:
1 Linear Prediction. Outline Windowing LPC Introduction to Vocoders Excitation modeling  Pitch Detection.
♥♥♥♥ 1. Intro. 2. VTS Var.. 3. Method 4. Results 5. Concl. ♠♠ ◄◄ ►► 1/181. Intro.2. VTS Var..3. Method4. Results5. Concl ♠♠◄◄►► IIT Bombay NCC 2011 : 17.
Speech Signal Representations I Seminar Speech Recognition 2002 F.R. Verhage.
Submitted By: Santosh Kumar Yadav (111432) M.E. Modular(2011) Under the Supervision of: Mrs. Shano Solanki Assistant Professor, C.S.E NITTTR, Chandigarh.
LPC-analysis-VOSIM-resynthesis Combined class December 18 th 2012 Johan & Peter Institute of Sonology Royal Conservatory, The Hague.
ECE 5525 Osama Saraireh Fall 2005 Dr. Veton Kepuska
EE Audio Signals and Systems Linear Prediction Kevin D. Donohue Electrical and Computer Engineering University of Kentucky.
VOCODERS. Vocoders Speech Coding Systems Implemented in the transmitter for analysis of the voice signal Complex than waveform coders High economy in.
Noise Reduction Two Stage Mel-Warped Weiner Filter Approach.
ITU-T G.729 EE8873 Rungsun Munkong March 22, 2004.
Outline Transmitters (Chapters 3 and 4, Source Coding and Modulation) (week 1 and 2) Receivers (Chapter 5) (week 3 and 4) Received Signal Synchronization.
1.INTRODUCTION The use of the adaptive codebook (ACB) in CELP-like speech coders allows the achievement of high quality speech, especially for voiced segments.
A Comparison Of Speech Coding With Linear Predictive Coding (LPC) And Code-Excited Linear Predictor Coding (CELP) By: Kendall Khodra Instructor: Dr. Kepuska.
More On Linear Predictive Analysis
SPEECH CODING Maryam Zebarjad Alessandro Chiumento Supervisor : Sylwester Szczpaniak.
Present document contains informations proprietary to France Telecom. Accepting this document means for its recipient he or she recognizes the confidential.
Voice Sampling. Sampling Rate Nyquist’s theorem states that a signal can be reconstructed if it is sampled at twice the maximum frequency of the signal.
By Sarita Jondhale 1 Signal preprocessor: “conditions” the speech signal s(n) to new form which is more suitable for the analysis Postprocessor: operate.
CELP / FS-1016 – 4.8kbps Federal Standard in Voice Coding
Institut für Nachrichtengeräte und Datenverarbeitung Prof. Dr.-Ing. P. Vary On the Use of Artificial Bandwidth Extension Techniques in Wideband Speech.
1 Speech Compression (after first coding) By Allam Mousa Department of Telecommunication Engineering An Najah University SP_3_Compression.
Motivation ● The (Ham) world needs an open source, patent free speech codec at bit rates of less than 5000 bit/s ● I know how to build one!
Chapter 13 Basic Audio Compression Techniques 13.1 ADPCM in Speech Coding 13.2 G.726 ADPCM 13.3 Vocoders 13.4 Further Exploration.
PATTERN COMPARISON TECHNIQUES
Figure 11.1 Linear system model for a signal s[n].
Automatic Speech Processing Project
Scalable Speech Coding for IP Networks
Digital Communications Chapter 13. Source Coding
Vocoders.
Chapter 13 Basic Audio Compression Techniques
Linear Prediction.
1 Vocoders. 2 The Channel Vocoder (analyzer) : The channel vocoder employs a bank of bandpass filters,  Each having a bandwidth between 100 HZ and 300.
Mohamed Chibani, Roch Lefebvre and Philippe Gournay
ON THE ARCHITECTURE OF THE CDMA2000® VARIABLE-RATE MULTIMODE WIDEBAND (VMR-WB) SPEECH CODING STANDARD Milan Jelinek†, Redwan Salami‡, Sassan Ahmadi*, Bruno.
Linear Predictive Coding Methods
Mobile Systems Workshop 1 Narrow band speech coding for mobile phones
A Study on Scalable CELP
Vocoders.
Linear Prediction.
Speech Processing Final Project
Fixed-point Analysis of Digital Filters
Presentation transcript:

Chapter 20 Speech Encoding by Parameters 20.1 Linear Predictive Coding (LPC) 20.2 Linear Predictive Vocoder 20.3 Code Excited Linear Prediction (CELP)

20.1 Linear Predictive Coding (1) Two kinds of correlation Short-time correlation between samples Long-time correlation between adjacent pitch periods. By Linear Prediction these correlations could be de-correlated and the residual signal will be obtained.

Linear Predictive Coding (2) Short-time Prediction of Speech The all poles model H(Z) = 1/A(Z)=1/[1-Σ a i Z -i ], i=1~P where {a i } are the predictive coefficients, P is the order number of the filter. In general, H(Z) is LP synthesis filter. A(Z) is LP analytic filter or inverse filter. P(Z)= Σ a i Z -i is the predictor of order P. For 8kHz sampling rate, P is typically The {a i } are obtained for every frame and updated with speed of per second (frame shift is 10-33ms).

Linear Predictive Coding (3) Long-time Prediction Filter 1/P(Z) represent the long-time correlations. The general form is 1/P(Z)=1/[1- Σ b i Z -(D+i) ], i=-q~r Delay parameter D equals pitch period, {b i } are predictive coefficients of long-time correlation. In general the number of b equals 1(q=r=0) to 3(q=r=1). D and {b i } could be extracted from speech signal or the residual signal obtained by removing the short-time correlation. These coefficients are updated with speed of per second.

Linear Predictive Coding (4) In some cases there is no the long-time prediction, only short-time prediction is done, then the long-time correlation is introduced into the LPC excitation model. Excitation Signal Source If the speech signal is input to the A(Z) and P(Z), the short-time and long-time correlations wil be removed and noise like signal is obtained that is the LP residual signal. If the speech is voiced, there exists the peak pulses repeated with pitch period. The spectrum of LP residual signal has much less fluctuation so it is possible to encode it with low rate.

Linear Predictive Coding (5) In general, the lower the rate is the worse the speech quality is or the lager the complexity is. In summary, LPC method encodes the pridictive coefficients (side information) and the excitation signal and outputs them at sending side; then decodes them and synthesizes the speech signals.

20.2 Linear Predictive Vocoder (1) The system using analysis and synthesis to encode the speech is called Vocoder. In LPC vocoder, Every frame (N samples) has P+3 parameters : {a i, i=1~P}, gain RMS, Voicing and pitch for voiced. It could implement low rate encoding with 2.4kb/s or less. LPC-10 Vocoder (1) Encoder (Fig.8-3) (2) RC(Reflection Coefficients) calculation (3) RMS calculation (average energy)

Linear Predictive Vocoder (2) (4) Pitch period extraction and unvoiced/voiced detection (5) Parameter encoding and decoding (6) Decoder at receive side (7) Comparison between the synthesized speech and primary speech (8) Problems of LPC-10 Vocoder

20.3 Code Excited Linear Prediction (CELP) (1) Initially proposed in Now there is a family of this algorithm. It features with high quality and low rate (4.8kb/s to 16kb/s). It encodes the frames. Frame length is 20~30ms. The encoding technique is based on search process of A-B-S, Perceptually Weighted VQ and LPC. The encoder is on Fig The key point is to search the optimal code vector and gain to minimize the perceptually weighted squared error of the origial signal and the synthesized signal.

Code Excited Linear Prediction (CELP) (2) CELP search algorithm US Standard FED-STD-1016