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Linear predictive coding

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Bundy, AlanWallen, Lincoln(1984).A Generilisation of the Glivenko-Canttelli Theorem.

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LPC is frequently used for transmitting spectral envelope information, and as such it has to be tolerant of transmission errors. Transmission of the filter coefficients directly (seelinear predictionfor definition of coefficients) is undesirable, since they are very sensitive to errors. In other words, a very small error can distort the whole spectrum, or worse, a small error might make the prediction filter unstable.

Linear predictive coding(LPC) is a tool used mostly inaudio signal processingandspeech processingfor representing thespectral envelopeof aofspeechincompressedform, using the information of a.[1]It is one of the most powerful speech analysis techniques, and one of the most useful methods for encoding good quality speech at a low bit rate and provides extremely accurate estimates of speech parameters.

This article includes alist of references, but

.Springer: 61.doi10.1007/978-3-642-96868-6_123.

Alexander, Amro El-Jaroudi (2003).Linear Predictive Coding.

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Because speech signals vary with time, this process is done on short chunks of the speech signal, which are called frames; generally 30 to 50 frames per second give intelligible speech with good compression.

LPC analyzes the speech signal by estimating the formants, removing their effects from the speech signal, and estimating the intensity and frequency of the remaining buzz. The process of removing the formants is called inverse filtering, and the remaining signal after the subtraction of the filtered modeled signal is called the residue.

This page was last edited on 3 September 2017, at 02:47.

From Wikipedia, the free encyclopedia

LPC is receiving some attention as a tool for use in the tonal analysis of violins and other stringed musical instruments.[2]

Robert M. Gray, IEEE Signal Processing Society, Distinguished Lecturer Program

LPC synthesis can be used to constructvocoderswhere musical instruments are used as excitation signal to the time-varying filter estimated from a singers speech. This is somewhat popular inelectronic musicPaul Lanskymade the well-known computer music piecenotjustmoreidlechatterusing linear predictive coding.[1]A 10th-order LPC was used in the popular 1980sSpeak & Spelleducational toy.

Tai, Hwan-Ching; Chung, Dai-Ting (June 14, 2012).Stradivari Violins Exhibit Formant Frequencies Resembling Vowels Produced by Females.

real-time LPC analysis/synthesis learning software

LPC is generally used for speech analysis and resynthesis. It is used as a form of voice compression by phone companies, for example in theGSMstandard. It is also used forsecurewireless, where voice must bedigitizedencryptedand sent over a narrow voice channel; an early example of this is the US governmentsNavajo I.

The numbers which describe the intensity and frequency of the buzz, the formants, and the residue signal, can be stored or transmitted somewhere else. LPC synthesizes the speech signal by reversing the process: use the buzz parameters and the residue to create a source signal, use the formants to create a filter (which represents the tube), and run the source through the filter, resulting in speech.

Deng, Li; Douglas OShaughnessy (2003).

Speech processing: a dynamic and optimization-oriented approach

Code-excited linear prediction(CELP)

Marcel Dekker. pp.4148.ISBN0-8247-4040-8.

LPC predictors are used inShortenMPEG-4 ALSFLACSILKaudio codec, and other lossless audio codecs.

There are more advanced representations such aslog area ratios(LAR),line spectral pairs(LSP) decomposition andreflection coefficients. Of these, especially LSP decomposition has gained popularity, since it ensures stability of the predictor, and spectral errors are local for small coefficient deviations.

LPC starts with the assumption that a speech signal is produced by a buzzer at the end of a tube (voiced sounds), with occasional added hissing and popping sounds (sibilantsandplosivesounds). Although apparently crude, this model is actually a close approximation of the reality of speech production. Theglottis(the space between the vocal folds) produces the buzz, which is characterized by its intensity (loudness) and frequency (pitch). The vocal tract (the throat and mouth) forms the tube, which is characterized by its resonances, which give rise toformants, or enhanced frequency bands in the sound produced. Hisses and pops are generated by the action of the tongue, lips and throat during sibilants and plosives.

. Wiley.doi10.1002/0471219282.eot155.

In 1972Bob KahnofARPA, with Jim Forgie (Lincoln Laboratory, LL) and Dave Walden (BBN Technologies), started the first developments in packetized speech, which would eventually lead toVoice over IPtechnology. In 1973, according to Lincoln Laboratory informal history, the first realtime 2400 bit/s LPC was implemented by Ed Hofstetter. In 1974 the first realtime two-way LPC packet speech communication was accomplished over the ARPANET at 3500 bit/s between Culler-Harrison and Lincoln Laboratory. In 1976 the first LPC conference took place over the ARPANET using theNetwork Voice Protocol, between Culler-Harrison, ISI, SRI, and LL at 3500 bit/s. And finally in 1978, B. S. Atal and Vishwanathet al.of BBN developed the firstvariable-rateLPC algorithm.

According toRobert M. GrayofStanford University, the first ideas leading to LPC started in 1966 when S. Saito and F. Itakura ofNTTdescribed an approach to automatic phoneme discrimination that involved the firstmaximum likelihoodapproach to speech coding. In 1967, John Burg outlined themaximum entropyapproach. In 1969 Itakura and Saito introducedpartial correlation, May Glen Culler proposed realtime speech encoding, andBishnu S. Atalpresented an LPC speech coder at the Annual Meeting of theAcoustical Society of America. In 1971 realtime LPC using 16-bit LPC hardware was demonstrated byPhilco-Ford; four units were sold.

30 years later Dr Richard Wiggins Talks Speak & Spell development

Alexander, OShaughnessy, D. (1998).

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