This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: Chapter 6: Modifying Sounds Using Loops 1 Chapter Objectives 2 How sound works: Acoustics, the physics of sound Sounds are waves of air pressure Sound comes in cycles The frequency of a wave is the number of cycles per second (cps), or Hertz Complex sounds have more than one frequency in them. The amplitude is the maximum height of the wave 3 Volume and Pitch: Psychoacoustics, the psychology of sound Our perception of volume is related (logarithmically) to changes in amplitude If the amplitude doubles, it’s about a 3 decibel (dB) change Our perception of pitch is related (logarithmically) to changes in frequency Higher frequencies are perceived as higher pitches We can hear between 5 Hz and 20,000 Hz (20 kHz) A above middle C is 440 Hz 4 “Logarithmically?” It’s strange, but our hearing works on ratios not differences, e.g., for pitch. We hear the difference between 200 Hz and 400 Hz, as the same as 500 Hz and 1000 Hz Similarly, 200 Hz to 600 Hz, and 1000 Hz to 3000 Hz Intensity (volume) is measured as watts per meter squared A change from 0.1W/m2 to 0.01 W/m2, sounds the same to us as 0.001W/m2 to 0.0001W/m2 5 Decibel is a logarithmic measure A decibel is a ratio between two intensities: 10 * log10(I1/I2) As an absolute measure, it’s in comparison to threshold of audibility 0 dB can’t be heard. Normal speech is 60 dB. A shout is about 80 dB 6 JES has a Sound MediaTool 7 Digitizing Sound: How do we get that into numbers? Remember in calculus, estimating the curve by creating rectangles? We can do the same to estimate the sound curve Analogtodigital conversion (ADC) will give us the amplitude at an instant as a number: a sample How many samples do we need? 8 Nyquist Theorem We need twice as many samples as the maximum frequency in order to represent (and recreate, later) the original sound. The number of samples recorded per second is the sampling rate If we capture 8000 samples per second, the highest frequency we can capture is 4000 Hz That’s how phones work If we capture more than 44,000 samples per second, we capture everything that we can hear (max 22,000 Hz) CD quality is 44,100 samples per second 9 Digitizing sound in the computer Each sample is stored as a number (two bytes) What’s the range of available combinations? 16 bits, 216 = 65,536 But we want both positive and negative values To indicate compressions and rarefactions. What if we use one bit to indicate positive (0) or negative (1)? That leaves us with 15 bits 15 bits, 215 = 32,768 One of those combinations will stand for zero We’ll use a “positive” one, so that’s one less pattern for positives 10 Two’s Complement Numbers 011 +3 Imagine there are only 3 bits 010 +2 we get 2 3 = 8 possible values 001 +1 Subtracting 1 from 2 we borrow 1 000 111 1 Subtracting 1 from 0 we borrow 1’s 110 2 which turns on the high bit for all 101 3 negative numbers 100 4 11 Two’s complement numbers can be simply added Adding 9 (11110111) and 9 (00001001) 12 +/ 32K...
View
Full
Document
This note was uploaded on 02/22/2012 for the course CS 177 taught by Professor Staff during the Fall '08 term at Purdue.
 Fall '08
 Staff

Click to edit the document details