Audio signal processing

Source: Wikipedia, the free encyclopedia.
"Audio processor" redirects here. For audio processing chips, see Sound chip.

Audio signal processing is a subfield of

sound power level is typically measured in decibels. As audio signals may be represented in either digital or analog
format, processing may occur in either domain. Analog processors operate directly on the electrical signal, while digital processors operate mathematically on its digital representation.

History

The motivation for audio signal processing began at the beginning of the 20th century with inventions like the

studio-to-transmitter links.[1] The theory of signal processing and its application to audio was largely developed at Bell Labs in the mid 20th century. Claude Shannon and Harry Nyquist's early work on communication theory, sampling theory and pulse-code modulation (PCM) laid the foundations for the field. In 1957, Max Mathews became the first person to synthesize audio from a computer, giving birth to computer music
.

Major developments in

audio coding formats such as MP3[9] and Advanced Audio Coding (AAC).[10]

Types

Analog

Further information: Analog signal processing

An analog audio signal is a continuous signal represented by an electrical voltage or current that is analogous to the sound waves in the air. Analog signal processing then involves physically altering the continuous signal by changing the voltage or current or charge via

electrical circuits
.

Historically, before the advent of widespread digital technology, analog was the only method by which to manipulate a signal. Since that time, as computers and software have become more capable and affordable, digital signal processing has become the method of choice. However, in music applications, analog technology is often still desirable as it often produces nonlinear responses that are difficult to replicate with digital filters.

Digital

Further information: Digital signal processing

A digital representation expresses the audio waveform as a sequence of symbols, usually

digital circuits such as digital signal processors, microprocessors and general-purpose computers. Most modern audio systems use a digital approach as the techniques of digital signal processing are much more powerful and efficient than analog domain signal processing.[11]

Applications

Processing methods and application areas include

reverb
removal or addition, etc.).

Audio broadcasting

See also: Broadcasting

Audio signal processing is used when broadcasting audio signals in order to enhance their fidelity or optimize for bandwidth or latency. In this domain, the most important audio processing takes place just before the transmitter. The audio processor here must prevent or minimize

shortwave broadcasting), and adjust overall loudness
to the desired level.

Active noise control

destructive interference
.

Audio synthesis

See also: Synthesizer

Audio synthesis is the electronic generation of audio signals. A musical instrument that accomplishes this is called a synthesizer. Synthesizers can either imitate sounds or generate new ones. Audio synthesis is also used to generate human speech using speech synthesis.

Audio effects

Main article: Effects unit

Audio effects alter the sound of a

reverb and delay
, which create echoing sounds and emulate the sound of different spaces.

Musicians,

electric or electronic instruments, they can be used with any audio source, such as acoustic instruments, drums, and vocals.[12][13]

Computer audition

This section is an excerpt from Computer audition.[edit]

Computer audition (CA) or machine listening is the general field of study of algorithms and systems for audio interpretation by machines.[14][15] Since the notion of what it means for a machine to "hear" is very broad and somewhat vague, computer audition attempts to bring together several disciplines that originally dealt with specific problems or had a concrete application in mind. The engineer Paris Smaragdis, interviewed in Technology Review, talks about these systems — "software that uses sound to locate people moving through rooms, monitor machinery for impending breakdowns, or activate traffic cameras to record accidents."[16]

Inspired by models of
human audition, CA deals with questions of representation, transduction, grouping, use of musical knowledge and general sound semantics for the purpose of performing intelligent operations on audio and music signals by the computer. Technically this requires a combination of methods from the fields of signal processing, auditory modelling, music perception and cognition, pattern recognition, and machine learning, as well as more traditional methods of artificial intelligence for musical knowledge representation.[17][18]

See also

References

  1. ISBN 0-471-79147-4.{{cite book}}: CS1 maint: multiple names: authors list (link
    )
  2. ^ US patent 2605361, C. Chapin Cutler, "Differential Quantization of Communication Signals", issued 1952-07-29 
  3. ISSN 1932-8346. Archived
    (PDF) from the original on 2022-10-09.
  4. ^ P. Cummiskey, Nikil S. Jayant, and J. L. Flanagan, "Adaptive quantization in differential PCM coding of speech", Bell Syst. Tech. J., vol. 52, pp. 1105—1118, Sept. 1973
  5. ISSN 0005-8580
    .
  6. S2CID 149806273. Archived
    (PDF) from the original on 2022-10-09.
  7. ^ J. P. Princen, A. W. Johnson und A. B. Bradley: Subband/transform coding using filter bank designs based on time domain aliasing cancellation, IEEE Proc. Intl. Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2161–2164, 1987.
  8. ISBN 9783319056609
    .
  9. ^ Guckert, John (Spring 2012). "The Use of FFT and MDCT in MP3 Audio Compression" (PDF). University of Utah. Archived (PDF) from the original on 2022-10-09. Retrieved 14 July 2019.
  10. ^ Brandenburg, Karlheinz (1999). "MP3 and AAC Explained" (PDF). Archived (PDF) from the original on 2017-02-13.
  11. ISBN 0-471-97226-6
    .
  12. ISBN 9781457415043
    .
  13. ISBN 9781931140065
    .
  14. ISBN 9781615209194
    .
  15. ^ "Machine Audition: Principles, Algorithms and Systems" (PDF).
  16. ^ Paris Smaragdis taught computers how to play more life-like music
  17. ISBN 978-3-540-57394-4
    .
  18. JSTOR 40285634
    .

Further reading
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