Lecture 2_winter_2012

Lecture - Digital Speech Processing Lecture 2 Review of DSP Fundamentals 1 What is DSP Input Signal Analog-toDigital Conversion Computer

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1 Digital Speech Processing— Lecture 2 Review of DSP Fundamentals
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2 What is DSP? Analog-to- Digital Conversion Computer Input Signal Output Signal Digital-to- Analog Conversion Digital • Method to represent a quantity, a phenomenon or an event • Why digital? Signal • What is a signal? – something (e.g., a sound, gesture, or object) that carries information – a detectable physical quantity (e.g., a voltage, current, or magnetic field strength) by which messages or information can be transmitted • What are we interested in, particularly when the signal is speech? Processing • What kind of processing do we need and encounter almost everyday? • Special effects?
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3 Common Forms of Computing Text processing – handling of text, tables, basic arithmetic and logic operations (i.e., calculator functions) – Word processing – Language processing – Spreadsheet processing – Presentation processing Signal Processing – a more general form of information processing, including handling of speech, audio, image, video, etc. – Filtering/spectral analysis – Analysis, recognition, synthesis and coding of real world signals – Detection and estimation of signals in the presence of noise or interference
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4 Advantages of Digital Representations Permanence and robustness of signal representations; zero- distortion reproduction may be achievable Advanced IC technology works well for digital systems Virtually infinite flexibility with digital systems – Multi-functionality – Multi-input/multi-output Indispensable in telecommunications which is virtually all digital at the present time Signal Processor Input Signal Output Signal A-to-D Converter D-to-A Converter
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5 Digital Processing of Analog Signals A-to-D conversion: bandwidth control, sampling and quantization Computational processing: implemented on computers or ASICs with finite-precision arithmetic basic numerical processing: add, subtract, multiply (scaling, amplification, attenuation), mute, … algorithmic numerical processing: convolution or linear filtering, non-linear filtering (e.g., median filtering), difference equations, DFT, inverse filtering, MAX/MIN, … D-to-A conversion: re-quantification* and filtering (or interpolation) for reconstruction x c ( t ) x [ n ] y [ n ] y c ( t ) A-to-D Computer D-to-A
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6 Discrete-Time Signals {[] } , () , , [] ( ) , A sequence of numbers Mathematical representation: Sampled from an analog signal, at time is called the and its recipr a a xx n n xt t n T xn x nT n T =− < < = < < sampling period, ± ± ± ± 1/ , 8000 1/ 8000 125 sec 10000 1/10000 100 sec 16000 1/16000 62.5 sec 20000 1/ 20000 50 sec ocal, is called the Hz Hz Hz Hz S S S S S FT μ = =↔ = = = = = = = = sampling frequency
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Speech Waveform Display 7 plot( ); stem( );
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8 Varying Sampling Rates Fs=8000 Hz Fs=6000 Hz Fs=10000 Hz
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Varying Sampling Rates 9 Fs=8000 Hz Fs=6000 Hz Fs=10000 Hz
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Quantization in out 0.3 0.9 1.5 2.1 2.4 1.8 1.2 0.6 7 6 5 4 3 2 1 0 A 3-bit uniform quantizer Quantization: • Transforming a continuously- valued input into a representation that assumes one out of a finite set of values • The finite set of output values is indexed; e.g., the value 1.8
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This note was uploaded on 12/29/2011 for the course ECE 259 taught by Professor Rabiner,l during the Fall '08 term at UCSB.