Editing Audio signal processing (section)

== Applications ==

Processing methods and application areas include [[audio storage|storage]], [[audio data compression|data compression]], [[music information retrieval]], [[speech processing]], [[acoustic location|localization]], [[detection theory|acoustic detection]], [[transmission (telecom)|transmission]], [[noise cancellation]], [[acoustic fingerprint]]ing, [[sound recognition]], [[synthesizer|synthesis]], and enhancement (e.g. [[Equalization (audio)|equalization]], [[audio filter|filtering]], [[audio level compression|level compression]], [[echo]] and [[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 [[overmodulation]], compensate for non-linear transmitters (a potential issue with [[medium wave]] and [[shortwave]] broadcasting), and adjust overall [[loudness]] to the desired level.

=== Active noise control ===

[[Active noise control]] is a technique designed to reduce unwanted sound. By creating a signal that is identical to the unwanted noise but with the opposite polarity, the two signals cancel out due to [[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 [[Physical modelling synthesis|imitate sounds]] or generate new ones. Audio synthesis is also used to generate human [[speech]] using [[speech synthesis]].

===Audio effects===
{{Main|Effects unit}}
Audio effects alter the sound of a [[musical instrument]] or other audio source. Common effects include [[Distortion (music)|distortion]], often used with electric guitar in [[electric blues]] and [[rock music]]; [[Dynamics (music)|dynamic]] effects such as [[volume pedal]]s and [[Audio compressor|compressors]], which affect loudness; [[Linear filter|filters]] such as [[wah-wah pedal]]s and [[graphic equalizer]]s, which modify frequency ranges; [[modulation]] effects, such as [[Chorus effect|chorus]], [[flanger]]s and [[Phaser (effect)|phasers]]; [[Pitch (music)|pitch]] effects such as [[Pitch shifter (audio processor)|pitch shifters]]; and time effects, such as [[reverb]] and [[Delay (audio effect)|delay]], which create echoing sounds and emulate the sound of different spaces.

Musicians, [[audio engineer]]s and record producers use effects units during live performances or in the studio, typically with electric guitar, bass guitar, [[electronic keyboard]] or [[electric piano]]. While effects are most frequently used with [[Electric instrument|electric]] or [[Electronic musical instrument|electronic]] instruments, they can be used with any audio source, such as [[Acoustic music|acoustic]] instruments, drums, and vocals.<ref>{{Cite book|last1=Horne|first1=Greg|url=https://books.google.com/books?id=cHALQ_CO5P0C|title=Complete Acoustic Guitar Method: Mastering Acoustic Guitar c|publisher=Alfred Music|year=2000|isbn=9781457415043|page=92}}</ref><ref>{{Cite book|last1=Yakabuski|first1=Jim|url=https://books.google.com/books?id=QwcLdjCCXHkC|title=Professional Sound Reinforcement Techniques: Tips and Tricks of a Concert Sound Engineer|publisher=Hal Leonard|year=2001|isbn=9781931140065|page=139}}</ref>

===Computer audition===
Computer audition (CA) or machine listening is the general field of study of [[Algorithm|algorithms]] and systems for audio interpretation by machines.<ref>{{cite book |url=http://www.igi-global.com/book/machine-audition-principles-algorithms-systems/40288 |title=Machine Audition: Principles, Algorithms and Systems |publisher=IGI Global |year=2011 |isbn=9781615209194}}</ref><ref>{{cite web |title=Machine Audition: Principles, Algorithms and Systems |url=http://epubs.surrey.ac.uk/596085/1/Wang_Preface_MA_2010.pdf}}</ref> 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 ''[[MIT Technology Review|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."<ref>[http://www.technologyreview.com/blog/VideoPosts.aspx?id=17438 Paris Smaragdis taught computers how to play more life-like music]</ref>

Inspired by models of [[Hearing (sense)|human audition]], CA deals with questions of representation, [[Transduction (machine learning)|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.<ref name="Tanguiane1993">{{Cite book |last=Tanguiane (Tangian) |first=Andranick |title=Artificial Perception and Music Recognition |date=1993 |publisher=Springer |isbn=978-3-540-57394-4 |series=Lecture Notes in Artificial Intelligence |volume=746 |location=Berlin-Heidelberg}}</ref><ref name="Tangian1994">{{Cite journal |last=Tanguiane (Tanguiane) |first=Andranick |year=1994 |title=A principle of correlativity of perception and its application to music recognition |journal=Music Perception |volume=11 |issue=4 |pages=465–502 |doi=10.2307/40285634 |jstor=40285634}}</ref>