At a purely physical level, sound is simply a mechanical disturbance of a medium. The medium in question may be air, solid, liquid, gas or a combination of several of these. This disturbance in the medium causes molecules to move back and forth in a spring-like manner. As one molecule hits the next, the disturbance moves through the medium causing sound to travel. These so called compressions and rarefactions in the medium can be described as sound waves. The simplest type of waveform, describing what is referred to as 'simple harmonic motion', is a sine wave.
Each time the waveform signal goes above 0 the molecules are in a state of compression meaning that each molecule within the waveform disturbance is pushing into its neighbour. Each time the waveform signal drops below 0 the molecules are in a state of rarefaction meaning the molecules are pulling away from thier neighbours. When a waveform shows a clear repeating pattern, as in the case above, it is said to be periodic. Periodic sounds give rise to the sensation of pitch.
Periodic waves have four common parameters, and each of the four parameters affects the way we perceive sound.
Period: This is the length of time it takes for a waveform to complete one cycle. This amount of time is referred to as t
Wavelength: the distance it takes for a wave to complete one full period. This is usually measured in meters.
Frequency: the number of cycles or periods per second. Frequency is measured in Hertz. If a sound has a frequency of 440Hz it completes 440 cycles every second. Given a frequency, one can easily calculate the period of any sound. Mathematically, the period is the reciprocal of the frequency (and vice versa). In equation form this is expressed as follows.
Frequency = 1/Period Period = 1/Frequency
Therefore the frequency is the inverse of the period, so a wave of 100 Hz frequency has a period of 1/100 or 0.01 secs, likewise a frequency of 256Hz has a period of 1/256, or 0.004 secs. To calculate the wavelength of a sound in any given medium we can use the following equation:
Wavelength = Velocity/Frequency
Humans can hear frequencies from 20Hz to 20000Hz (although this can differ dramatically from individual to individual and the upper limit will decay with age). You can read more about frequency in the next chapter.
Phase: This is the starting point of a waveform. The starting point along the Y-axis of our plotted waveform is not always zero. This can be expressed in degrees or in radians. A complete cycle of a waveform will cover 360 degrees or (2 x pi) radians.
Amplitude: Amplitude is represented by the y-axis of a plotted pressure wave. The strength at which the molecules pull or push away from each other, which will also depend upon the resistance offered by the medium, will determine how far above and below zero - the point of equilibrium - the wave fluctuates. The greater the y-value the greater the amplitude of our wave. The greater the compressions and rarefactions, the greater the amplitude.
The analogue sound waves we hear in the world around us need to be converted into an electrical signal in order to be amplified or sent to a soundcard for recording. The process of converting acoustical energy in the form of pressure waves into an electrical signal is carried out by a device known as a a transducer.
A transducer, which is usually found in microphones, produces a changing electrical voltage that mirrors the changing compression and rarefaction of the air molecules caused by the sound wave. The continuous variation of pressure is therefore 'transduced' into continuous variation of voltage. The greater the variation of pressure the greater the variation of voltage that is sent to the computer.
Ideally the transduction process should be as transparent as possible: whatever goes in should come out as a perfect analogue in a voltage representation. In reality however this will not be the case, noise and distortion are always incorporated into the signal. Every time sound passes through a transducer or is transmitted electrically a change in signal quality will result. When we talk of 'noise' we are talking specifically about any unwanted signal captured during the transduction process. This normally manifests itself as an unwanted 'hiss'.
The analogue voltage that corresponds to an acoustic signal changes continuously so that at each instant in time it will have a different value. It is not possible for a computer to receive the value of the voltage for every instant because of the physical limitations of both the computer and the data converters (remember also that there are an infinite number of instances between every two instances!).
What the soundcard can do, however, is to measure the power of the analogue voltage at intervals of equal duration. This is how all digital recording works and this is known as 'sampling'. The result of this sampling process is a discrete, or digital, signal which is no more than a sequence of numbers corresponding to the voltage at each successive moment of sampling.
Below left is a diagram showing a sinusoidal waveform. The vertical lines that run through the diagram represents the points in time when a snapshot is taken of the signal. After the sampling has taken place we are left with what is known as a discrete signal consisting of a collection of audio samples, as illustrated in the diagram on the right hand side below. If one is recording using a typical audio editor the incoming samples will be stored in the computer's RAM (Random Access Memory). In Csound one can process the incoming audio samples in real time and output a new stream of samples or write them to disk in the form of a sound file.
It is important to remember that each sample represents the amount of voltage, positive or negative, that was present in the signal at the point in time at which the sample or snapshot was taken.
The same principle applies to recording of live video: a video camera takes a sequence of pictures of motion and most video cameras will take between 30 and 60 still pictures a second. Each picture is called a frame and when these frames are played in sequence at a rate corresponding to that at which they were taken we no longer perceive them as individual pictures, we perceive them instead as a continuous moving image.
In general, analogue systems can be quite unreliable when it comes to noise and distortion. Each time something is copied or transmitted some noise and distortion is introduced into the process. If this is repeated many times, the cumulative effect can deteriorate a signal quite considerably. It is for this reason that the music industry has almost entirely turned to digital technology. One particular advantage of storing a signal digitally is that once the changing signal has been converted to a discrete series of values, it can effectively be 'cloned' an clones can be made of that clone with no loss or distortion of data. Mathematical routines can be applied to prevent errors in transmission, which could otherwise introduce noise into the signal.
The sample rate describes the number of samples (pictures/snapshots) taken each second. To sample an audio signal correctly it is important to pay attention to the sampling theorem:
"To represent digitally a signal containing frequencies up to X Hz, it is necessary to use a sampling rate of at least 2X samples per second"
According to this theorem, a soundcard or any other digital recording device will not be able to represent any frequency above 1/2 the sampling rate. Half the sampling rate is also referred to as the Nyquist frequency, after the Swedish physicist Harry Nyquist who formalized the theory in the 1920s. What it all means is that any signal with frequencies above the Nyquist frequency will be misrepresented and will actually produce a frequency lower than the one being sampled. When this happens it results in what is known as 'aliasing' or 'foldover'.
Here is a graphical representation of aliasing.
The sinusoidal waveform in blue is being sampled where arrows are indicated along the timeline. The line that joins the red circles together is the captured waveform. As you can see, the captured waveform and the original waveform express different frequencies.
Here is another example:
We can see that if the sample rate is 40,000 there is no problem with sampling a signal that is 10KHz. On the other hand, in the second example it can be seen that a 30kHz waveform is not going to be correctly sampled. In fact we end up with a waveform that is 10kHz, rather than 30kHz. This may seem like an academic proposition in that we will never be able to hear a 30KHz waveform anyway but some synthesis and DSP techniques procedures will produce these frequencies as unavoidable by-products and we need to ensure that they do not result in unwanted artifacts.
The following Csound instrument plays a 1000 Hz tone first directly, and then because the frequency is 1000 Hz lower than the sample rate of 44100 Hz:
<CsoundSynthesizer> <CsOptions> -odac </CsOptions> <CsInstruments> ;example by Joachim Heintz sr = 44100 ksmps = 32 nchnls = 2 0dbfs = 1 instr 1 asig oscils .2, p4, 0 outs asig, asig endin </CsInstruments> <CsScore> i 1 0 2 1000 ;1000 Hz tone i 1 3 2 43100 ;43100 Hz tone sounds like 1000 Hz because of aliasing </CsScore> </CsoundSynthesizer>
The same phenomenon takes places in film and video too. You may recall having seen wagon wheels apparently turn at the wrong speed in old Westerns. Let us say for example that a camera is taking 60 frames per second of a wheel moving. In one example, if the wheel is completing one rotation in exactly 1/60th of a second, then every picture looks the same and as a result the wheel appears to be motionless. If the wheel speeds up, i.e. it increases its rotational frequency, it will appear as if the wheel is slowly turning backwards. This is because the wheel will complete more than a full rotation between each snapshot.
As an aside, it is worth observing that a lot of modern 'glitch' music intentionally makes a feature of the spectral distortion that aliasing induces in digital audio. Csound is perfectly capable of imitating the effects of aliasing while being run at any sample rate - if that is what you desire.
Audio-CD Quality uses a sample rate of 44100Kz (44.1 kHz). This means that CD quality can only represent frequencies up to 22050Hz. Humans typically have an absolute upper limit of hearing of about 20Khz thus making 44.1KHz a reasonable standard sampling rate.
All digital computers represent data as a collection of bits (short for binary digit). A bit is the smallest possible unit of information. One bit can only be in one of two states - off or on, 0 or 1. The meaning of the bit - which can represent almost anything - is unimportant at this point, the thing to remember is that all computer data - a text file on disk, a program in memory, a packet on a network - is ultimately a collection of bits.
Bits in groups of eight are called bytes, and one byte usually represents a single character of data in the computer. It's a little used term, but you might be interested in knowing that a nibble is half a byte (usually 4 bits).
All digital computers work in a environment that has only two variables, 0 and 1. All numbers in our decimal system therefore must be translated into 0's and 1's in the binary system. If you think of binary numbers in terms of switches. With one switch you can represent up to two different numbers.
0 (OFF) = Decimal 0
1 (ON) = Decimal 1
Thus, a single bit represents 2 numbers, two bits can represent 4 numbers, three bits represent 8 numbers, four bits represent 16 numbers, and so on up to a byte, or eight bits, which represents 256 numbers. Therefore each added bit doubles the amount of possible numbers that can be represented. Put simply, the more bits you have at your disposal the more information you can store.
Apart from the sample rate, another important attribute that can affect the fidelity of a digital signal is the accuracy with which each sample is known, its resolution or granularity. Every sample obtained is set to a specific amplitude (the measure of strength for each voltage) level. Each voltage measurement will probably have to be rounded up or down to the nearest digital value available. The number of levels available depends on the precision of the measurement in bits, i.e. how many binary digits are used to store the samples. The number of bits that a system can use is normally referred to as the bit-depth resolution.
If the bit-depth resolution is 3 then there are 8 possible levels of amplitude that we can use for each sample. We can see this in the diagram below. At each sampling period the soundcard plots an amplitude. As we are only using a 3-bit system the resolution is not good enough to plot the correct amplitude of each sample. We can see in the diagram that some vertical lines stop above or below the real signal. This is because our bit-depth is not high enough to plot the amplitude levels with sufficient accuracy at each sampling period.
example here for 4, 6, 8, 12, 16 bit of a sine signal ... ... coming in the next release
The standard resolution for CDs is 16 bit, which allows for 65536 different possible amplitude levels, 32767 either side of the zero axis. Using bit rates lower than 16 is not a good idea as it will result in noise being added to the signal. This is referred to as quantization noise and is a result of amplitude values being excessively rounded up or down when being digitized. Quantization noise becomes most apparent when trying to represent low amplitude (quiet) sounds. Frequently a tiny amount of noise, known as a dither signal, will be added to digital audio before conversion back into an analogue signal. Adding this dither signal will actually reduce the more noticeable noise created by quantization. As higher bit depth resolutions are employed in the digitizing process the need for dithering is reduced. A general rule is to use the highest bit rate available.
Many electronic musicians make use of deliberately low bit depth quantization in order to add noise to a signal. The effect is commonly known as 'bit-crunching' and is relatively easy to implement in Csound.
The entire process, as described above, of taking an analogue signal and converting it to a digital signal is referred to as analogue to digital conversion, or ADC. Of course digital to analogue conversion, DAC, is also possible. This is how we get to hear our music through our PC's headphones or speakers. For example, if one plays a sound from Media Player or iTunes the software will send a series of numbers to the computer soundcard. In fact it will most likely send 44100 numbers a second. If the audio that is playing is 16 bit then these numbers will range from -32768 to +32767.
When the sound card receives these numbers from the audio stream it will output corresponding voltages to a loudspeaker. When the voltages reach the loudspeaker they cause the loudspeaker's magnet to move inwards and outwards. This causes a disturbance in the air around the speaker - the compressions and rarefactions introduced at the beginning of this chapter - resulting in what we perceive as sound.
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