Clicks

Clicks are various types of short-duration, transient sounds that contain significant high-frequency energy that originate from electronic equipment. Malfunctioning analog equipment, loose analog cable connections, connecting and disconnecting analog cables, and digital audio synchronization errors are all causes of unwanted clicks.

Clicks resulting from analog equipment malfunction can often be random and sporadic, making it difficult to identify their exact source. In this case, meters can be helpful to indicate which audio channel contains a click, especially if clicks are present in the absence of program material. A peak hold meter can be invaluable in chasing down a problematic piece of equipment, because the meter holds the peak level if we happen to miss seeing it when the click occurs.

Loose or dirty analog connections may randomly break a connection, causing dropouts, clicks, and sporadic noise bursts. When we make analog connections in a patch bay or directly on a piece of equipment, we create signal discontinuities and therefore also clicks and pops. Breaking a phantom powered microphone signal can make a particularly loud pop or click that can damage not only the microphone but also any loudspeakers that may try to reproduce the loud click.

With digital connections between equipment, it is important to ensure that sampling rates are identical across all interconnected equipment and that clock sources are consistent. Without properly selected clock sources in digital audio, clicks are inevitable and will likely occur at some regular interval, usually spaced by several seconds. Clicks that originate from improper clock sources are often fairly subtle, and they require vigilance to identify them aurally. Depending on the digital interconnections in a studio, the clock source for each device needs to be either internal, digital input, or word clock.

Pops

Pops are transient thump-like sounds that typically have more significant low-frequency energy than clicks. Usually pops occur as a result of vocal plosives that are produced in front of a microphone. Plosives are consonant sounds, such as those that result from pronouncing the letters p, b, and d, in which a singer or speaker produces a burst of air when producing these consonant sounds. If you hold your hand up in front of your mouth and make a “p” sound, you can feel the little burst of air coming from your mouth. When this burst of air reaches a microphone capsule, the microphone produces a low-frequency, thump-like sound. Usually we try to counter pops during vocal recording by placing a pop filter in front of a vocal microphone. Pop filters are usually made of thin, acoustically transparent fabric stretched across a circular frame.

We do not hear pops from a singer when we listen acoustically in the same space as the singer. The pop artifact is purely a result of a microphone’s response to a burst of air produced by a vocalist. Pops distract listeners from a vocal performance because they are not expecting to hear a low-frequency thump from a singer. Even if the song has a kick drum in the mix, often a vocalist’s pop will not line up with a kick drum hit. We can filter out a pop with a high-pass filter, making sure the cutoff frequency is low enough not to affect low harmonics in the voice, or inserted only during the brief moment while a pop is sounding.

Listen for low-frequency thumps when recording, mixing, or providing live sound reinforcement for sung or spoken voice. In live sound situations, the best way to remove pops is to turn on a high-pass filter on the respective mixer channel or turn on the high-pass filter on the microphone itself if it has one.

Hum and Buzz

Improperly grounded analog circuits and signal chains can cause noise in the form of hum or buzz that is introduced into analog audio signals. Both are related to the frequency of electrical alternating current (AC) power sources, also referred to as mains frequency in some places. The frequency of a power source will be either 50 Hz or 60 Hz depending on geographic location and the power source being used. Power distribution in North America is 60 Hz, in Europe it is 50 Hz, in Japan it will be either 50 or 60 Hz depending on the specific location within the country, and in most other countries it is 50 Hz.

When a ground problem is present, there is either a hum or a buzz generated with a fundamental frequency equal to the power source alternating current frequency, 50 or 60 Hz, with additional harmonics above the fundamental. A hum is identified as a sound containing primarily just lower harmonics and buzz as that which contains mainly higher harmonics.

We want to make sure we identify any hum or buzz before recording, when the problem is easier to solve. Trying to remove such noises in postproduction is possible but will take extra time. Because a hum or buzz often includes numerous harmonics of 50 or 60 Hz, a number of narrow notch filters are needed, each tuned to a harmonic, to effectively remove all of the offending sound. Sometimes this is the only option to remove the offending noise, but these notch filters also affect our program material, of course.

Hum can also be caused by electromagnetic interference (EMI). If we place audio cables (especially those carrying microphone level signals) alongside power cables, the power cables can induce hum in the adjacent audio lines. An audio cable’s proximity to power cables matters, so the farther away the two can be, the better. If they do need to cross, try to make the crossing a 90-degree angle to reduce the strength of the electromagnetic field that crosses the audio cable. Although we are not going to discuss the exact technical and wiring problems that can cause hum and buzz and how such problems might be solved, there are many excellent references that cover the topic in great detail, such as Giddings’s book titled Audio Systems Design and Installation, a classic reference that has recently been republished.

One of the best ways we can check for low-level ground hum is to bring up monitor levels with microphones on and powered but while musicians are not playing. If we eventually apply dynamic range compression with makeup gain to an audio signal, what was once inaudible low-level noise could be much more audible. If we can apprehend any ground hum before getting to that stage, our recording will be much cleaner.

Extraneous Acoustic Sounds

Despite the hope for perfectly quiet recording spaces, there are often numerous sources of noise both inside and outside of a recording space that we must deal with. Some of these are relatively constant, steady-state sounds, such as air-handling noise, whereas other sounds are unpredictable and somewhat random, such as car horns, people talking, footsteps, noise from storms, or simply when we drop items or bump a microphone stand in the studio.

With most of the population concentrated in cities, sound isolation can be particularly challenging as noise levels rise and our physical proximity to others increases. Besides airborne noise there is also structure-borne noise, where vibrations are transmitted through building structures and end up producing sound in our recording spaces. Professionally built recording studios are often constructed with what is called floating floors and room-in-room construction to maximize sound isolation.

Keep your ears open for extraneous acoustic sounds. They can pop up at seemingly random times. We need to monitor our audio constantly to identify them.

Radio Frequency Interference (RFI)

Radio station and cell phone signals are sometimes demodulated down to the audio range and then amplified by our audio equipment. With radio station interference we hear what a local FM radio station is broadcasting. The resulting audio is mainly high-frequency content, but it is annoying and distracting nonetheless. Cell phone interference usually sounds like a series of bzzt, bzzt, bzzt sounds. Encourage everyone in your recording space to turn off cell phones or set them to airplane mode.

With all of the noise types I describe above, the best defense is to catch them by ear when we are recording, and try to eliminate the sources of the noise if possible, or wait for them to pass, before doing any more recording. Noise reduction software is very sophisticated and highly effective now, but noise removal is still a manual process that takes time. If we can avoid recording offending noise in the first place, we save ourselves time in post-production.

Hard Clipping and Overload

Figure 5.3 A sine wave at 1 kHz that has been hard clipped. Note the sharp edges of the waveform that did not exist in the original sine wave.

Hard clipping occurs when we apply enough gain to a signal for it to reach the limits of a device’s maximum input or output level. Peak signal levels greater than a device’s maximum allowable signal level are flattened, creating new harmonics that were not present in the original waveform. For example, if a sine wave (Figure 5.1) is clipped, the result is a square wave whose time domain waveform now contains sharp edges (Figure 5.3). Without getting into a detailed mathematical discussion of Fourier analysis, we can simply say that the sharp corners and steep vertical portions of a clipped sine waveform indicate the presence of high-frequency harmonics. We could confirm this by doing frequency-domain analysis of a square wave with a fast Fourier transform (FFT) analyzer. The frequency content includes new harmonics (multiples of the fundamental sine tone frequency). A square wave is a specific type of waveform that is composed of odd-numbered harmonics (first, third, fifth, seventh, ninth, eleventh, and so on). A sine tone, on the other hand, is a single frequency. A 1 kHz square wave contains the following frequencies: 1 kHz, 3 kHz, 5 kHz, 7 kHz, 9 kHz, and all subsequent odd multiples of 1 kHz up to the bandwidth of the device. Furthermore, as we go up in harmonic number, each subsequent harmonic’s amplitude decreases in level.

As we said earlier, distortion increases the harmonics present in an audio signal. Because of the additional high harmonics that are added to a signal when it is distorted, the timbre becomes brighter and harsher. Clipping a signal flattens out the peaks of a waveform, adding sharp corners to a clipped peak. The new sharp corners in the time domain waveform represent increased high-frequency harmonic content in the signal.

Soft Clipping

A milder form of distortion known as soft clipping or overdrive is often used for creative effect on an audio signal. Its timbre is often much less harsh than hard clipping. As we can see from Figure 5.4, the shape of an overdriven sine wave has flat tops but does not have the sharp corners that are present in a hard-clipped sine wave (Figure 5.3). The sharp corners in the hard-clipped tone would indicate more high-frequency energy than in a soft-clipped sine tone.

Hard-clipping distortion is produced when a signal’s amplitude rises above the maximum output level of an amplifier. With gain stages such as solid-state microphone preamplifiers, there is an abrupt change in timbre and sound quality as a signal rises from the clean, linear gain region to a higher level that causes clipping. Once a signal reaches the maximum level of a gain stage, it cannot go any higher regardless of any increase in input level; thus there are flattened peaks as we discussed above. It is the abrupt switch from clean amplification to hard clipping that introduces such harsh-sounding distortion. Some types of amplifiers, such as those with vacuum tubes or valves, exhibit a more gradual transition from linear gain to hard clipping. This gradual transition in the gain range produces a very desirable soft clipping with rounded edges in the waveform, as shown in Figure 5.4. This is the main reason why guitarists often prefer tube guitar amplifiers to solid-state amplifiers: the distortion is often richer and warmer. Soft clipping from tubes adds more possibilities for expressivity than clean sounds alone. In pop and rock recordings especially, there are examples of the creative use of soft clipping and overdrive that enhance sounds and create new and interesting timbres.

Figure 5.4 A sine wave at 1 kHz that has been soft clipped or overdriven. Note how the waveform has curved edges, with a shape that is somewhere between that of the original sine wave and a square wave.

Quantization Error Distortion

In the process of converting an analog signal to the standard digital pulse-code modulation (PCM) representation, analog amplitude levels for each sample get quantized to a finite number of steps. The maximum number of quantization steps available to represent analog voltage levels is determined by an analog-to-digital converter’s bit resolution, that is, the number of bits of data stored per sample, also called the bit depth. An analog-to-digital converter records and stores sample values using binary digits, or bits, and the more bits available, the more quantization steps possible.

The Red Book standard for CD-quality audio specifies 16 bits per sample, which represents 2 ¹⁶ or 65,536 possible steps from the highest positive voltage level to the lowest negative value. Usually higher bit depths are chosen for the initial stage of a recording. Given the choice, most recording engineers will record using at least 24 bits per sample, which corresponds to 2 ²⁴ or 16,777,216 possible amplitude steps between the highest and lowest analog voltages. Even if the final product is only 16 bits, it is still better to record initially at 24 bits because any gain change or signal processing applied will require requantization. The more quantization steps that are available to start with, the more accurate our representation of an analog signal will be.

Each quantized step of linear PCM digital audio is an approximation of the original analog signal. There are a fixed number of quantization steps but theoretically an infinite number of analog levels. Because quantization steps are approximations of the original analog levels, there will be some amount of error in any digital representation. Quantization error is essentially a distortion of our audio signal. We can minimize or eliminate quantization error distortion by applying dither, with or without noise shaping, which randomizes the error. With the random error produced by dither, distortion is replaced by very low-level noise, which is generally considered to be preferable over distortion.

The interesting thing about the amplitude quantization process is that the signal-to-error ratio drops as signal level is reduced. In other words, the error becomes more significant for lower-level signals. For each 6 dB that a signal is below the maximum recording level of digital audio (0 dBFS), 1 bit of binary representation is lost. For each bit lost, the number of quantization steps is halved. A signal recorded at 16 bits per sample at an amplitude of − 12 dBFS will only be using 14 of the 16 bits available, representing a total of 16,384 (or 2 ¹⁴) quantization steps.

Even if the signal peaks of a recording are near the 0 dBFS level, there are often other lower-level sounds within a mix that can suffer from quantization error. Wide dynamic range recordings may include significant sections where audio signals hover well below 0 dBFS. One example of low-level sound within a recording is reverberation and the sense of space that it creates. With excessive quantization error, perhaps as the result of bit depth reduction, some of the sense of depth and width that is conveyed by reverberation is lost. By randomizing quantization error with the use of dither during bit depth reduction, some of the lost sense of space and reverberation can be reclaimed, but with the cost of some added noise.

Sometimes engineers use bit depth reduction as a distortion effect. Often called a bit-crusher, the plug-in simply re-quantizes an audio signal with fewer bits. Figure 5.5 shows a sine wave that has been quantized with 3 bits, giving 8 (or 2 ³) discrete amplitude steps. Close observation of the bit-crushed sine tone waveform shows that there are more negative values than positive values. This is because we have an even number of discrete amplitude steps and the midpoint must be at 0.

Figure 5.5 A sine wave at 1 kHz that has been quantized with 3 bits, giving 8 (or 2 ³) steps. Plot (A) shows the waveform as a digital audio workstation would show it, as a continuous, if jagged, line. In reality, plot (B) is a more accurate representation because we only know the signal level at each sample point. The time between each sample point is undefined.

Exercise: Comparing Linear PCM to Encoded Audio

Once we begin to explore the ways perceptual encoders degrade sound quality, we may find it easier to identify these artifacts in a broader range of situations. In other words, once we know what to listen for, we start hearing them almost everywhere. One of the ways we can investigate sound quality degradation is to compare linear PCM sound files to their encoded versions to identify any audible differences. We can use free software, such as Apple’s iTunes Player and Microsoft’s Windows Media Player, to encode our audio. Sound quality deficiencies in encoded audio may not be immediately obvious unless we are tuned into the types of artifacts that codecs produce.

According to generally accepted practices for scientific perceptual evaluation, the best way to hear differences between two audio signals is to switch back and forth between them. Immediate switching between stimuli with no pause helps us hear differences easier than waiting several minutes or hours between stimuli. Once we begin to learn to hear the kinds of artifacts an encoder is producing, they become easier to hear without doing a side-by-side comparison of encoded to linear PCM.

Start by encoding a linear PCM audio file at various bit rates in MP3, AAC, or WMA and try to identify how your audio signal is degraded. Lower bit rates result in a smaller file size, but they also reduce the quality of the audio. Different codecs—MP3, AAC, and WMA—provide slightly different results for a given bit rate because although the general principles are similar, the specific encoding algorithms vary from codec to codec. Switch back and forth between the original linear PCM audio and the encoded version. Try encoding recordings from different genres of music. Note the sonic artifacts that are produced for each bit rate and encoder. Listen for the artifacts and sound quality issues I listed above.

Another option is to compare streaming audio from online sources to linear PCM versions that you may have. Most online radio stations and music players (with some exceptions, such as TIDAL, which can play lossless audio) are using lower bit-rate audio containing more clearly audible encoding artifacts than is found with audio from other sources such as through the iTunes Store.

Exercise: Subtraction

Another interesting exercise we can do is to subtract an encoded audio file from a linear PCM version of the same audio file. To complete this exercise, convert a linear PCM file to some encoded form and then convert it back to linear PCM at the same sampling rate. Import the original sound file and the encoded/decoded file (now linear PCM) into a digital audio workstation (DAW), on two different stereo tracks, taking care to line them up in time precisely, to the sample level if possible. Playing back the synchronized stereo tracks together, reverse the polarity (of both left and right channels) of the encoded/decoded file so that it is subtracted from the original. Provided the two stereo tracks are lined up accurately in time, anything that is common to both tracks will cancel, and the remaining audio that we hear is the difference between the original audio and the audio encoded by the codec. Doing this exercise helps highlight the types of artifacts that are present in encoded audio.

Exercise: Listening to Encoded Audio through Mid-Side Processing

By splitting an encoded file into its mid and side (M-S) components, some of the artifacts created by the encoding process can be uncovered. The perceptual encoding process relies on masking to hide artifacts that are created in the process. When a stereo recording is converted to M and S components and the M component is removed, artifacts typically become much more audible. In many recordings, especially in the pop/rock genre, the M component forms the majority of the audio signal and can mask a great deal of encoding artifacts. By listening to only the S component, codec artifacts become much more audible.

Try encoding an audio file with a perceptual encoder at a common bit rate such as 128 kbps and decoding it back into linear PCM (WAV or AIFF). It is possible to use the “Technical Ear Trainer—Mid-Side” software module to hear the effect that M-S decoding can have on highlighting the effects of a codec. All of the “Technical Ear Trainer” software modules are available on the companion website: www.routledge.com/cw/corey.

Summary

In this chapter we explored some of the undesirable sounds that can make their way into a recording. Although distortion as an effect can offer endless creative possibilities, unintentional distortion from overloading can take the life out of our audio. By practicing with the included distortion software ear-training module and completing the exercises, we can become more aware of some common forms of distortion with the goal of correcting them when they occur. Although there is excellent noise and distortion reduction software available, we save ourselves time in post-production by catching noise and distortion that may occur during the recording process.