'Cepstral coefficients' presentation slideshows

LSA 352 Speech Recognition and Synthesis

LSA 352 Speech Recognition and Synthesis. Dan Jurafsky. Lecture 6: Feature Extraction and Acoustic Modeling.

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Linear Prediction

Linear Prediction. Linear Prediction (Introduction) :. The object of linear prediction is to estimate the output sequence from a linear combination of input samples, past output samples or both : The factors a(i) and b(j) are called predictor coefficients.

517 views • 39 slides

Concepts of Multimedia Processing and Transmission

Concepts of Multimedia Processing and Transmission. IT 481, Lecture #4 Dennis McCaughey, Ph.D. 25 September, 2006. Introduction to Linear Systems. The Modified Discrete Cosine Transform (MDCT) was introduced in the lecture on MP3 encoding

515 views • 35 slides

Chairman:Hung-Chi Yang Presenter: Yue -Fong Guo Advisor: Dr. Yeou-Jiunn Chen Date: 2013.3.20

Classification of place of articulation in unvoiced stops with spectro -temporal surface modeling . V. Karjigi , P. Rao Dept. of Electrical Engineering, Indian Institute of Technology Bombay, Powai , Mumbai 400076, India

332 views • 19 slides

Human Factor Cepstral Coefficients: Biological Inspiration + Engineering = Noise-robust Speech Features

Human Factor Cepstral Coefficients: Biological Inspiration + Engineering = Noise-robust Speech Features. Mark D. Skowronski and John G. Harris Computational Neuro-Engineering Lab University of Florida Gainesville, FL, USA. Outline. Speech Recognition: Man vs Machine

288 views • 12 slides

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106 views • 10 slides