'Speech signals' presentation slideshows

Bayesian Decision Theory (Sections 2.1-2.2)

1.49k views • 88 slides

A 12-WEEK PROJECT IN Speech Coding and Recognition

A 12-WEEK PROJECT IN Speech Coding and Recognition. by Fu-Tien Hsiao and Vedrana Andersen. Overview. An Introduction to Speech Signals (Vedrana) Linear Prediction Analysis (Fu) Speech Coding and Synthesis (Fu) Speech Recognition (Vedrana). Speech Coding and Recognition.

692 views • 53 slides

A 12-WEEK PROJECT IN Speech Coding and Recognition

A 12-WEEK PROJECT IN Speech Coding and Recognition. by Fu-Tien Hsiao and Vedrana Andersen. Overview. An Introduction to Speech Signals (Vedrana) Linear Prediction Analysis (Fu) Speech Coding and Synthesis (Fu) Speech Recognition (Vedrana). Speech Coding and Recognition.

530 views • 53 slides

Senior Capstone Project Integration of Matlab Tools for DSP Code Generation

Senior Capstone Project Integration of Matlab Tools for DSP Code Generation. ECE Department March 2nd, 2006. Team Members: Kwadwo Boateng and Charles Badu Advisors: Professor Thomas Stewart and Dr Inn Soo Ahn. Project Outline Project Summary Current Status Filter Implementation

622 views • 40 slides

Waveform SpeechCoding Algorithms: An Overview

Waveform SpeechCoding Algorithms: An Overview. June 20 th , 2012 Adel Zaalouk. Outline. Introduction Concepts Quantization PCM DPCM ADPCM Standards & Applications G711 G726 Performance Comparison & Examples Summary & Conclusion.

508 views • 35 slides

3 . Introduction to Signal and Systems

Term 332. EE3 0 1 0 : Signals and Systems Analysis. 3 . Introduction to Signal and Systems. Dr. Mujahed Al- Dhaifallah. Lecture Objectives. General properties of signals Energy and power for continuous & discrete-time signals Signal transformations Specific signal types.

864 views • 29 slides

Cellular Communications

Cellular Communications. 5. Speech Coding. Low Bit-rate Voice Coding. Voice is an analogue signal Needed to be transformed in a digital form (bits) Speech signal is not random=>can be encoded using fewer bits as compared to random signal

385 views • 29 slides

Cellular Communications

Cellular Communications. 5. Speech Coding. Low Bit-rate Voice Coding. Voice is an analogue signal Needed to be transformed in a digital form (bits) Speech signal is not random=>can be encoded using fewer bits as compared to random signal

399 views • 29 slides

Machine Translation at DARPA

Machine Translation at DARPA. Joseph Olive Program Manager. Agenda. Pre-GALE Programs and Studies DARPA and the Language Community GALE Plans GALE MT Evaluation GALE Accomplishments Future Research. Language Research at DARPA. Four Decades of Research Continuous progress

524 views • 26 slides

LINEAR DYNAMIC MODEL FOR CONTINUOUS SPEECH RECOGNITION

LINEAR DYNAMIC MODEL FOR CONTINUOUS SPEECH RECOGNITION. Ph.D. Candidate: Tao Ma Advised by: Dr. Joseph Picone Institute for Signal and Information Processing (ISIP) Mississippi State University. Abstract.

369 views • 24 slides

Beate Peter

Chapter 3 Biological Substrates of Speech Development: A Brief Synopsis of the Developing Neuromuscular System. Beate Peter. Introduction. Speech is the finishing stage of transducing a thought into sound waves

394 views • 23 slides

Reduction of Additive Noise in the Digital Processing of Speech

Reduction of Additive Noise in the Digital Processing of Speech. Avner Halevy AMSC 664 Final Presentation May 2009 Dr. Radu Balan Department of Mathematics Center for Scientific Computation and Math. Modeling. Background and Goal. Digital speech signals

347 views • 21 slides

Linear Predictive Coding for Speech Compression

Linear Predictive Coding for Speech Compression . Dev Ghosh ECE 463. 9 March 2006. Overview. General Model for Speech Synthesis Channel Vocoder Linear Predictive Coder (LPC-10) Code Excited Linear Prediction (CELP) Novel Application Sub-band adaptive filtering based on cochlear model.

977 views • 18 slides

speech, played several metres from the listener in a room

speech, played several metres from the listener in a room - seems to have the same phonetic content as when played nearby - that is, perception is constant however, amount of reverberation varies with distance: - so temporal envelopes of speech signals vary considerably,

258 views • 18 slides

LECTURE 17: FAST FOURIER TRANSFORM

LECTURE 17: FAST FOURIER TRANSFORM. Objectives: Discrete Fourier Transform Computational Complexity Decimation in Time Butterfly Diagrams Convolution Application Waterfall Plots Spectrograms

350 views • 14 slides

Numerical Text-to-Speech Synthesis System

Numerical Text-to-Speech Synthesis System. Presentation By: Sevakula Rahul Kumar. Presentation Outline. Introduction Background 3 Components of TTS System Text Pre-processing Prosody Concatenation What has been done / Future Work Questions. What is a TTS System?.

261 views • 13 slides

Numerical Text-to-Speech Synthesis System

Numerical Text-to-Speech Synthesis System. Presentation By: Sevakula Rahul Kumar. Presentation Outline. Introduction Background 3 Components of TTS System Text Pre-processing Prosody Concatenation What has been done / Future Work Questions. What is a TTS System?.

285 views • 13 slides

Presents Fall Forum 2002

257 views • 12 slides

Bayesian Enhancement of Speech Signals

Bayesian Enhancement of Speech Signals. Jeremy Reed. Outline. Speech Model Bayes application MCMC algorithm Results. Speech Model. Predict current speech sample from p previous samples (AR process) Justified by physics Lossless acoustic tubes Time for vocal tract to change shape

278 views • 11 slides

Auto-Regressive Hidden Markov Models

94 views • 2 slides