INTRO COMPUTER MUSIC
INTRO COMPUTER MUSIC MUSC 336
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This 6 page Class Notes was uploaded by Caden Wolf PhD on Monday October 26, 2015. The Class Notes belongs to MUSC 336 at University of South Carolina - Columbia taught by R. Bain in Fall. Since its upload, it has received 31 views. For similar materials see /class/229503/musc-336-university-of-south-carolina-columbia in Music at University of South Carolina - Columbia.
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Date Created: 10/26/15
BAIN MUSC 336 Introduction to Music Technology MIDI MUSICAL INSTRUMENT DIGITAL INTERFACE MIDI data is simply a series of number values from 0 to 255 that allow control events to be universally understood by different hardware and software Peter Kirn Real World Dig ital Audio Terms and Concepts Note Messages Note7onNote7off pair 7 Note7on command 7 Note7off command Note number 07127 Key velocity 0 and 17127 7 Attack velocity 7 Release velocity Channel number 1716 Channel Messages Aftertouch 7 Polyphonic 7 Channel Control change 7 Continuous 0763 7 Noncontinuous 647127 Pitch bend Program change 7 Bank 7 Program number System Messages System common System real7time System7exclusive SYSEX Devices Keyboard Controller keyboard Alternate controller Broadcast channel Polyphony Modes Global System Instrument Multitimbral Song and Sequencing Adding Expressivity Expression pedal Modulation wheel Pitch7bend wheel Sustain pedal Data Baud rate Byte 8 bits 7 Data 07127 7 Status Numeric notation 7 Binary MIDI data format MIDI data rate 3125 kb MIDI event MSBLSB Pulse per quarter PPQ Standard MIDI Fi1eSMF 7 Type 0 7 Type 1 Important Control Change Numbers 1 7 Modulation wheel 7 7 Volume 10 7 Pan 64 7 Sustain pedal 123 7 All notes off Interconnection 57pin DIN connector Apple s AudioMIDI Setup Master controller slave Daisy chain MIDI INOUTTHRU ports MIDI interface 2X2 4X4 etc Synchronization EBU MIDI Time Code MTC and MIDI Clock SMPTE Standards OpenSound Control OSC General MIDI GM 7 GM Instrument Library 7 GM Perc Key Map MIDI 10 Specification MIDI Implementation Chart National Association of Music Merchants NAMM Reading Charles Dodge and Thomas lerse Standard Interfaces for Musical Devices in Computer Music Synthesis Composition and Performance New York SchirIner 1995 407712 Peter Kim Real World Digital Audio Berkeley Peachpit Press 2006 85791 2937303 324725 MIDI Page 1 of 2 BAIN MUSC 336 Introduction to Music Technology Quotable Striking a key on a clavier produces a threeibyte MIDI data sequence a Note On command followed by the note key number to indicate pitch and then a numerical value that is a measurement of the key velocity imparted by the performer When multiple keys are struck to play a chord the commands are sent in the order the keys are depressed Releasing a key also initiates a threeibyte sequence a Note O command followed by the number of the note that has been turned off and a numerical value that indicates how quickly the key returns to its original position System realitime messages are used to synchronize MIDI devices with start stop and continue commands that control a sequence of events There is also a MIDI timing clock that transmits a pulse 24 times per quarter note relative to the current tempo The MIDI standard provides a definition of MIDI Time code MTC which can be used to synchronize MIDI compatible devices MTC contains an absolute description of the time in hours minutes seconds and fractions of a second To make the timing of the data unambiguous to the receiver an 87bit byte of data is framed by a start bit and a stop bit each data byte actually requires 10 bits to travel down the circuit one after the other As another costisaving measure the MIDI communications bus is essentially unidirectional so that it does not promote twoiway conversations between devices Charles Dodge and Thomas lerse Computer Music When you go beyond the realm of pedals keyboards and faders MIDI s rigid way of defining music performance can get awkward fast the data bandwidth of MIDI is painfully narrow and MIDI uses absurdly small rigid chunks of data Peter Kirn Real World Dig ital Audio MIDI Page 2 of 2 BAIN MUSC 336 Introduction to Music Technology Music and Computers CH 3 THE FREQUENCY DOMAIN TERMS AND CONCEPTS In order ofappearance 31 Frequency Domain vectors 34 The DFT FFT and IFFT domains 7 magnitude Discrete Fourier Transform 7 amplitude 7 direction DFT 7 time vector addition Fast Fourier transform FFT 7 frequency Inverse Fast Fourier transform envelopes Sampling and Fourier IFFT 7 transients Expansion sample rate attack stage Fourier expansion frame size as a power of 2 decay stage Fourier coeficients number of bins release stage bins bin width 7 steady state stage waterfall 3D plot windowing 7 average signal envelope histogram of frequencies 7 peak signal envelope 33 Fourier and the Sum of root7mean7squared RMS Sines number of bins frame Size 2 amplitude Jean Baptiste Fourier 17687 running window technique 1830 bin width f range of bins sonogram f vs t basic waveshapes melograph pitch vs t 7 sine 35 Problems with the phonophotography 7 sawtooth FFTIFFT 7 square timefrequency resolution trade7 32 Phasors 7 triangle off phasor representation of a sine 7 pulse lobes wave complex waveform time smearing sound analysis spectrum digital manipulation of sound infinite series 36 Some Alternatives to the sine wave model Fourier series FFT phasor function Fourier analysis synthesis and wavelet analysis trigonometric functions transform McAulay7Quatieri MQ degrees Fourier coefficients Analysis radians 7 low order angular velocity of the phasor 7 high order Software law of superposition adding dc term Benjamin Faber s SignalScope phasors filters Tom Erbe s SoundHack Fourier s theorem 7 low pass Kelly Fitz s Lemur Pro periodic function 7 high pass Pacific Tech s Graphing fundamental frequency 7 band pass Calcu overtones partials and hydrophone armonics odd7partial symmetry Text Burk Phil Larry Polansky Douglas Repetto Mary Roberts and Dan Rockmore Music and Computers A Theoretical and Historical Approach Emeryville CA Key College Publishing 2005 Reference Philip Greenspun Fourier Analysis in Curtis Roads The ComputerMusic Tutor39ml Cambridge MA MIT Press 1999 107371112 lVIusic and Computers Ch 3 Page 1 BAIN MUSC 336 Introduction to Music Technology Fourier Series fa A0 EA Sin27 nwt 23 cos2n nwt nl Quotable FOURIER THEORY French scientist and mathematician Jean Baptiste Fourier 176871830 proved that any periodic waveform can be expressed as the sum of an infinite set of sine waves The frequencies of these sine waves must be integer multiples of some fundamental frequency A periodic znction is any function that looks like the infinite repetition of some fixed pattern Any sound can be represented as a combination of phaseishifted amplitudeimodulated tones of differing frequencies If a periodic function has a period T the length of the repeated waveform pattern it s frequency f is 1 T lT is called the tndanwnial equency of the periodic function the decomposition of an acoustic waveform into its component partials is called Fourier expansion PHASOR A phasor is essentially a way of representing a sinusoidal function any sound not just periodic ones can be represented as a sum of sinusoids called a Fourier series FFI An FFT of a time domain signal takes the samples and gives us a new set of numbers representing the frequencies amplitudes and phases of the sine waves that make up the sound we ve analyzed FFTtakes a chunk of time called a frame a certain number of samples and considers that chunk to be a single period of a repeating waveform The reason this works is that most sounds are locally stationary meaning that over any short period of time the sound really does look like a repeating function a bin is a discrete slice or band of the frequency spectrum they are not based on the frequency of the sound itself but on the sampling rate frequency perception is logarithmic so a fixed bin size gives us worse resolution at the low frequencies and better resolution at higher frequencies The more accurately we want to measure the frequency content of a signal the more samples we have to analyze in each frame of the FFT Yet the larger the frame the less we know about the temporal events that take place within that frame if the highest frequency is B times the fundamental then you only need ZB 1 samples to determine the Fourier coefficients A transform takes a list of the sample values and turn the values into a new list of numbers that describes a possible new way to add up different basic sounds AIusic and Computers Ch 3 Page 2 AlN MUSC Irmaduailm It Music Techmilligy The Phasor anesenmtion of a Sine Wave 1 1 t J Figs 1 2 and 3 Components of the phasor representation in 39 h spins 39 elocity 39 triangle from Fig 1 a This angle may he 1 39 39 39 39 39 39 39Fi sThfuntinallrlwttra n I of SLYIJASOldal wavebrm Notice that at any time I the wine of 9 is so 2m For example after 5 sec at it or mo degrees The table below shows five values of so in both radians and degrees for four different wines of t The height of the phasor at time t is given by the following equation ht r Si U 2m Notice that the radius r of the circle in Fig 1 corresponds with the the amplitude A of the phasor in g 3 The number of To ht A sinw 2m lt1gt 39 39 Fourier anal i Note that the traditional expression of the Fourier S2712 ft AEl i A sin27t mot i B cos27t mot l with the same frequency This can he expressed mathematically as A sinwt B coswt C sirlwt lt1gt Musw and Computers 01 3 Page 3 BAIN MUSC 336 Introduction to Music Technology AIusic and Computers Ch 3 Page 4
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