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Students need to train their hearing to discern tonal differences between corrected and uncorrected files. They must also recognize aural changes as they adjust a plug-in’s parameters so they can hear if the changes are too extreme.Students will identify the tonal differences between two audio files, apply the appropriate signal processing, and evaluate the results.
Improving the aural skills of novice recording engineers so they can apply corrective signal processing is a crucial goal of any Recording Arts program. Traditionally, this skill is taught by playing reference recordings through signal processors, constructive criticism of a student’s recording project, or A/B comparisons of disparate sounds.
Unfortunately, this tradition has several limitations. Few audio departments own enough signal processors so that an entire class can operate them individually. Furthermore, even if this limitation was addressed, there are too many possible positions for the processor’s controls—an instructor cannot ensure that all of the processor’s settings are identical. This inconsistency will confuse many beginning students.
My department’s first solution to this problem was preparing many prerecorded examples on audio CDs for students to compare in class. While this is a step in the right direction, this limits an instructor to the examples and processor settings recorded; he cannot alter them in real time while explaining their purpose.
Today, most computer-based audio recording programs include plug-in algorithms that emulate common signal processors: reverberators, equalizers, and dynamic range processors. After preparing suitable audio files that need effective signal processing, students can use Digital Performer, for example, to compare the defective sounds with corrected versions, experiment with plug-in processor settings and correct them.
Computer-based audio recording program—A software application that, with the aid of an audio interface, records sounds and allows the user to edit, process, correct or otherwise change the audio data. Digital Performer, Pro Tools, Cubase, Cakewalk, Sound Forge, Peak, Nuendo and Spark are example of this software.
Signal Processors—External audio devices that alter the quality of the incoming audio signal. Compressors, gates, equalizers, reverberators, chorusers, flangers and delays are examples of signal processors.
Plug-in—Most modern audio recording software include ‘plug-ins’ that emulate signal processors. These functions are called ‘plug-ins’ be cause they are inserted into the signal path of the audio file. Most modern plug-ins function in real time so that one hears the result of a setting change as it is made.
Compressors—a signal processor that lowers the loudest portion (or raises the softest portion) of a recording. Compressors reduce the overall dynamic range of a sound so one can amplify it without overloading a signal path.
Limiters—a type of compressor that keeps amplitudes from exceeding a user specified level.
Expander—a signal processor that lowers the softest portion of the recording, usually the ambient noise or decay of the sound. Expanders increase the dynamic range of a recording by making ambient noise softer while leaving loud sounds unchanged.
Gate—a type of expander that eliminates ambient sounds by making the softest portions of a recording silent. This device ‘opens’ and ‘closes’ according to the strength of the sound, hence the name ‘gate.’
Reverberator—A signal processor that adds echo and reverberation to a recording. The amount, strength, length and quality of this effect is usually user adjustable.
Equalizer—A signal processor that increases or decreases energy in a specific f requency band. Tone controls are simple equalizers that raise or lower the bass or treble portion of a sound. Most recording equalizers fall into two groups: parametric equalizers or graphic equalizers
1. Digital Performer 2.7 (or higher) software.
2. Macintosh G3 or better.
3. Audio files containing defects suitable for signal processing.
Relevance to Academia and Industry
Computer-based training provides an effective way to train novice engineer’s hearing with controlled conditions and procedures. By limiting which parameter the student can adjust, an instructor can better focus the lab to certain goals. Graduates that can hear and correct sound defects are very valuable to the recording and sound reinforcement industry.