Editing Speech coding (section)

== Modern speech compression ==
Much of the later work in speech compression was motivated by military research into digital communications for [[Secure voice|secure military radios]], where very low data rates were used to achieve effective operation in a hostile radio environment. At the same time, far more [[processing power]] was available, in the form of [[Very Large Scale Integration|VLSI circuits]], than was available for earlier compression techniques. As a result, modern speech compression algorithms could use far more complex techniques than were available in the 1960s to achieve far higher compression ratios.

The most widely used speech coding algorithms are based on [[linear predictive coding]] (LPC).<ref>{{cite journal |last1=Gupta |first1=Shipra |title=Application of MFCC in Text Independent Speaker Recognition |journal=International Journal of Advanced Research in Computer Science and Software Engineering |date=May 2016 |volume=6 |issue=5 |pages=805–810 (806) |s2cid=212485331 |issn=2277-128X |url=https://pdfs.semanticscholar.org/2aa9/c2971342e8b0b1a0714938f39c406f258477.pdf |archive-url=https://web.archive.org/web/20191018231621/https://pdfs.semanticscholar.org/2aa9/c2971342e8b0b1a0714938f39c406f258477.pdf |url-status=dead |archive-date=2019-10-18 |access-date=18 October 2019}}</ref> In particular, the most common speech coding scheme is the LPC-based [[code-excited linear prediction]] (CELP) coding, which is used for example in the [[GSM]] standard. In CELP, the modeling is divided in two stages, a [[linear prediction|linear predictive]] stage that models the spectral envelope and a code-book-based model of the residual of the linear predictive model. In CELP, linear prediction coefficients (LPC) are computed and quantized, usually as [[line spectral pairs]] (LSPs). In addition to the actual speech coding of the signal, it is often necessary to use [[channel coding]] for transmission, to avoid losses due to transmission errors. In order to get the best overall coding results, speech coding and channel coding methods are chosen in pairs, with the more important bits in the speech data stream protected by more robust channel coding.

The [[modified discrete cosine transform]] (MDCT) is used in the LD-MDCT technique used by the [[AAC-LD]] format introduced in 1999.<ref name="Schnell">{{cite conference |last1=Schnell|first1=Markus |last2=Schmidt |first2=Markus |last3=Jander |first3=Manuel |last4=Albert |first4=Tobias |last5=Geiger |first5=Ralf |last6=Ruoppila |first6=Vesa |last7=Ekstrand |first7=Per |last8=Bernhard |first8=Grill |date=October 2008 |title=MPEG-4 Enhanced Low Delay AAC - A New Standard for High Quality Communication |url=https://www.iis.fraunhofer.de/content/dam/iis/de/doc/ame/conference/AES-125-Convention_AAC-ELD-NewStandardForHighQualityCommunication_AES7503.pdf |conference=125th AES Convention |publisher=[[Audio Engineering Society]] |access-date=20 October 2019 |website=[[Fraunhofer IIS]]}}</ref> MDCT has since been widely adopted in [[voice-over-IP]] (VoIP) applications, such as the [[G.729.1]] [[wideband audio]] codec introduced in 2006,<ref name="Nagireddi">{{cite book |last1=Nagireddi |first1=Sivannarayana |title=VoIP Voice and Fax Signal Processing |date=2008 |publisher=[[John Wiley & Sons]] |isbn=9780470377864 |page=69 |url=https://books.google.com/books?id=5AneeZFE71MC&pg=PA69}}</ref> [[Apple Inc.|Apple]]'s [[FaceTime]] (using AAC-LD) introduced in 2010,<ref name="AppleInsider standards 1">{{cite web|url=http://www.appleinsider.com/articles/10/06/08/inside_iphone_4_facetime_video_calling.html|date=June 8, 2010|access-date=June 9, 2010|title=Inside iPhone 4: FaceTime video calling|publisher=[[AppleInsider]]|author=Daniel Eran Dilger}}</ref> and the [[CELT]] codec introduced in 2011.<ref name="presentation">[http://people.xiph.org/~greg/video/linux_conf_au_CELT_2.ogv Presentation of the CELT codec] {{Webarchive|url=https://web.archive.org/web/20110807182250/http://people.xiph.org/~greg/video/linux_conf_au_CELT_2.ogv |date=2011-08-07 }} by Timothy B. Terriberry (65 minutes of video, see also [http://www.celt-codec.org/presentations/misc/lca-celt.pdf presentation slides] in PDF)</ref>

[[Opus (audio format)|Opus]] is a [[free software]] audio coder. It combines the speech-oriented LPC-based [[SILK]] algorithm and the lower-latency MDCT-based CELT algorithm, switching between or combining them as needed for maximal efficiency.<ref name="homepage">{{cite web |url = https://opus-codec.org/ |title=Opus Codec |work=Opus |publisher=Xiph.org Foundation |type=Home page |access-date=July 31, 2012 }}</ref><ref>{{cite conference |last1=Valin |first1=Jean-Marc |last2=Maxwell |first2=Gregory |last3=Terriberry |first3=Timothy B. |last4=Vos |first4=Koen |title=High-Quality, Low-Delay Music Coding in the Opus Codec |conference=135th AES Convention |publisher=[[Audio Engineering Society]] |date=October 2013 |arxiv=1602.04845 }}</ref> It is widely used for VoIP calls in [[WhatsApp]].<ref name="Register">{{cite news |last1=Leyden |first1=John |title=WhatsApp laid bare: Info-sucking app's innards probed |url=https://www.theregister.co.uk/2015/10/27/whatsapp_forensic_analysis/ |access-date=19 October 2019 |work=[[The Register]] |date=27 October 2015}}</ref><ref name="Hazra">{{cite book |last1=Hazra |first1=Sudip |last2=Mateti |first2=Prabhaker |chapter=Challenges in Android Forensics |editor-last1=Thampi |editor-first1=Sabu M. |editor-last2=Pérez |editor-first2=Gregorio Martínez |editor-last3=Westphall |editor-first3=Carlos Becker |editor-last4=Hu |editor-first4=Jiankun |editor-last5=Fan |editor-first5=Chun I. |editor-last6=Mármol |editor-first6=Félix Gómez |title=Security in Computing and Communications: 5th International Symposium, SSCC 2017 |date=September 13–16, 2017 |publisher=Springer |isbn=9789811068980 |pages=286–299 (290) |doi=10.1007/978-981-10-6898-0_24 |chapter-url=https://books.google.com/books?id=1u09DwAAQBAJ&pg=PA290}}</ref><ref name="Srivastava">{{cite book |last1=Srivastava |first1=Saurabh Ranjan |last2=Dube |first2=Sachin |last3=Shrivastaya |first3=Gulshan |last4=Sharma |first4=Kavita |chapter=Smartphone Triggered Security Challenges: Issues, Case Studies and Prevention |editor-last1=Le |editor-first1=Dac-Nhuong |editor-last2=Kumar |editor-first2=Raghvendra |editor-last3=Mishra |editor-first3=Brojo Kishore |editor-last4=Chatterjee |editor-first4=Jyotir Moy |editor-last5=Khari |editor-first5=Manju |title=Cyber Security in Parallel and Distributed Computing: Concepts, Techniques, Applications and Case Studies |date=2019 |publisher=John Wiley & Sons |isbn=9781119488057 |pages=187–206 (200) |doi=10.1002/9781119488330.ch12 |s2cid=214034702 |chapter-url=https://books.google.com/books?id=FzGtDwAAQBAJ&pg=PA200}}</ref> The [[PlayStation 4]] video game console also uses Opus for its [[PlayStation Network]] system party chat.<ref name="playstation">{{cite web|url=https://doc.dl.playstation.net/doc/ps4-oss/ |title=Open Source Software used in PlayStation4 |publisher=Sony Interactive Entertainment Inc. |access-date=2017-12-11}}{{failed verification|reason=Source does not indicate how Opus is used|date=September 2022}}</ref>

A number of codecs with even lower [[bit rate]]s have been demonstrated. [[Codec2]], which operates at bit rates as low as {{nowrap|450 bit/s}}, sees use in amateur radio.<ref>{{cite web |title=GitHub - Codec2 |website=[[GitHub]] |date=November 2019 |url=https://github.com/x893/codec2}}</ref> NATO currently uses [[MELPe]], offering intelligible speech at {{nowrap|600 bit/s}} and below.<ref>Alan McCree, “A scalable phonetic vocoder framework using joint predictive vector quantization of MELP parameters,” in Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, 2006, pp. I 705–708, Toulouse, France</ref> Neural vocoder approaches have also emerged: [[Lyra (codec)|Lyra]] by Google gives an "almost eerie" quality at {{nowrap|3 kbit/s}}.<ref name=":0">{{Cite web |last=Buckley |first=Ian |date=2021-04-08 |title=Google Makes Its Lyra Low Bitrate Speech Codec Public |url=https://www.makeuseof.com/google-lyra-speech-codec-public/ |access-date=2022-07-21 |website=MakeUseOf |language=en-US}}</ref> Microsoft's [[Satin (codec)|Satin]] also uses machine learning, but uses a higher tunable bitrate and is wideband.<ref name=":3">{{Cite web |last=Levent-Levi |first=Tsahi |date=2021-04-19 |title=Lyra, Satin and the future of voice codecs in WebRTC |url=https://bloggeek.me/lyra-satin-webrtc-voice-codecs/ |access-date=2022-07-21 |website=BlogGeek.me |language=en-US}}</ref>

===Sub-fields===
; [[Wideband audio]] coding
* [[Linear predictive coding]] (LPC)
** [[AMR-WB]] for [[WCDMA]] networks
** [[VMR-WB]] for [[CDMA2000]] networks
** [[Speex]], IP-MR, [[SILK]] (part of [[Opus (audio format)|Opus]]), and [[Unified Speech and Audio Coding|USAC/xHE-AAC]] for VoIP and [[videoconferencing]]
* [[Modified discrete cosine transform]] (MDCT)
** [[AAC-LD]], [[G.722.1]], [[G.729.1]], [[CELT]] and [[Opus (audio format)|Opus]] for VoIP and videoconferencing
* [[Adaptive differential pulse-code modulation]] (ADPCM)
** [[G.722]] for VoIP
* Neural speech coding
** [[Lyra (codec)|Lyra]] (Google): V1 uses neural network reconstruction of log-mel spectrogram; V2 is an end-to-end [[autoencoder]].
** [[Satin (codec)|Satin]] (Microsoft)
** LPCNet (Mozilla, Xiph): neural network reconstruction of LPC features<ref>{{cite web |title=LPCNet: Efficient neural speech synthesis |url=https://github.com/xiph/LPCNet |publisher=Xiph.Org Foundation |date=8 August 2023}}</ref>

; [[Narrowband]] audio coding
* LPC
** [[FNBDT]] for military applications
** [[Selectable Mode Vocoder|SMV]] for [[CDMA]] networks
** [[Full Rate]], [[Half Rate]], [[Enhanced full rate|EFR]] and [[Adaptive Multi-Rate audio codec|AMR]] for [[GSM]] networks
** [[G.723.1]], [[G.728]], [[G.729]], [[G.729.1]] and [[iLBC]] for VoIP or videoconferencing
* ADPCM
** [[G.726]] for VoIP
* [[Multi-Band Excitation]] (MBE)
** [[Multi-Band Excitation|AMBE+]] for [[digital radio|digital]] [[mobile radio]] and [[satellite phone]]
** [[Codec 2]]