Audio Error Detection
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citations to reliable sources. Unsourced material may be challenged and removed. (August 2008) (Learn how and when to remove this template message) In information theory and coding theory with applications in computer science and telecommunication, error detection and error detection and correction audio correction or error control are techniques that enable reliable delivery of digital data over
Error Detection And Correction Techniques
unreliable communication channels. Many communication channels are subject to channel noise, and thus errors may be introduced during transmission from the error detection and correction codes in digital electronics source to a receiver. Error detection techniques allow detecting such errors, while error correction enables reconstruction of the original data in many cases. Contents 1 Definitions 2 History 3 Introduction 4 Implementation 5 Error detection error detection in data link layer schemes 5.1 Repetition codes 5.2 Parity bits 5.3 Checksums 5.4 Cyclic redundancy checks (CRCs) 5.5 Cryptographic hash functions 5.6 Error-correcting codes 6 Error correction 6.1 Automatic repeat request (ARQ) 6.2 Error-correcting code 6.3 Hybrid schemes 7 Applications 7.1 Internet 7.2 Deep-space telecommunications 7.3 Satellite broadcasting (DVB) 7.4 Data storage 7.5 Error-correcting memory 8 See also 9 References 10 Further reading 11 External links Definitions[edit] The general definitions of the terms are
Error Detection And Recovery Takes Place At Which Layer
as follows: Error detection is the detection of errors caused by noise or other impairments during transmission from the transmitter to the receiver. Error correction is the detection of errors and reconstruction of the original, error-free data. History[edit] The modern development of error-correcting codes in 1947 is due to Richard W. Hamming.[1] A description of Hamming's code appeared in Claude Shannon's A Mathematical Theory of Communication[2] and was quickly generalized by Marcel J. E. Golay.[3] Introduction[edit] The general idea for achieving error detection and correction is to add some redundancy (i.e., some extra data) to a message, which receivers can use to check consistency of the delivered message, and to recover data determined to be corrupted. Error-detection and correction schemes can be either systematic or non-systematic: In a systematic scheme, the transmitter sends the original data, and attaches a fixed number of check bits (or parity data), which are derived from the data bits by some deterministic algorithm. If only error detection is required, a receiver can simply apply the same algorithm to the received data bits and compare its output with the received check bits; if the values do not match, an error has occurred at some point during the transmission. In a system that uses a non-systematic cod
mm. As illustrated below, typical dust particles are much smaller than that. As the laser is further focused down to about 1.7 micrometers at the depth of the pits, any shadow from the error detection at the data link level is achieved by small defects is blurred and indistinct and does not cause a read error. Larger defects error detection and correction in computer networks are handled by error-correcting codes in the handling of the digital data. IndexCD conceptsSound reproduction conceptsReferenceRossingPhysics Teacher, Dec. 87 HyperPhysics***** Sound
Error Detection And Correction Ppt
R Nave Go Back Error-Correction of CD Signals The data on a compact disc is encoded in such a way that some well- developed error-correction schemes can be used. A sophisticated error- correction code known as CIRC (cross https://en.wikipedia.org/wiki/Error_detection_and_correction interleave Reed-Solomon code) is used to deal with both burst errors from dirt and scratches and random errors from inaccurate cutting of the disc. The data on the disc are formatted in frames which contain 408 bits of audio data and another 180 bits of data which include parity and sync bits and a subcode. A given frame can contain information from other frames and the correlation between frames can be used to minimize errors. Errors http://hyperphysics.phy-astr.gsu.edu/hbase/audio/cdplay4.html on the disc could lead to some output frequencies above 22kHz (half the sampling frequency of 44.1 kHz) which could cause serious problems by "aliasing" down to audible frequencies. A technique called oversampling is used to reduce such noise. Using a digital filter to sample four times and average provides a 6-decibel improvement in signal-to-noise ratio. For more details, see the references. IndexCD conceptsSound reproduction conceptsReferencesRossingPhysics Teacher, Dec. 87Myaoka HyperPhysics***** Sound R Nave Go Back Data Encoding on Compact Discs When the laser in a compact disc player sweeps over the track of pits which represents the data, a transition from a flat area to a pit area or vice versa is interpreted as a binary 1, and the absence of a transition in a time interval called a clock cycle is interpreted as a binary 0. This kind of detection is called an NRZI code. The particular NRZI code used with compact discs is EFM (eight-to-fourteen modulation) in which eight bits of data are represented by fourteen channel bits. In addition to the actual digital sound data, parity and sync bits and a subcode are also recorded on the disc in "frames" . In a given frame, 408 bits of audio data are recorded with another 180 bits of data which permit a sophisticated error-correction code to be used. A given frame can
a compressed and modulated DAB audio stream comprising a plurality of audio frames encoded with scale factors and a DAB-CRC error detection code for https://www.google.ch/patents/US8533551 indicating errors in the scale factors; demodulating the http://publications.csail.mit.edu/abstracts/abstracts07/sybor/sybor.html DAB stream; and processing...https://www.google.ch/patents/US8533551?utm_source=gb-gplus-sharePatent US8533551 - Audio error detection and processing Erweiterte PatentsucheTry the new Google Patents, with machine-classified Google Scholar results, and Japanese and South Korean patents. VeröffentlichungsnummerUS8533551 B2PublikationstypErteilung AnmeldenummerUS 12/451,741 PCT-NummerPCT/IL2007/000656 error detection Veröffentlichungsdatum10. Sept. 2013Eingetragen30. Mai 2007 Prioritätsdatum30. Mai 2007Auch veröffentlicht unterUS20100205516, WO2008146271A1 Veröffentlichungsnummer12451741, 451741, PCT/2007/656, PCT/IL/2007/000656, PCT/IL/2007/00656, PCT/IL/7/000656, PCT/IL/7/00656, PCT/IL2007/000656, PCT/IL2007/00656, PCT/IL2007000656, PCT/IL200700656, PCT/IL7/000656, PCT/IL7/00656, PCT/IL7000656, PCT/IL700656, US 8533551 B2, US 8533551B2, US-B2-8533551, US8533551 B2, US8533551B2 ErfinderItsik Abudi, Roy OrenUrsprünglich BevollmächtigterSiano Mobile error detection and Silicon Ltd.Zitat exportierenBiBTeX, EndNote, RefManPatentzitate (8), Nichtpatentzitate (2), Referenziert von (2), Klassifizierungen (4), Juristische Ereignisse (4) Externe Links:USPTO, USPTO-Zuordnung, EspacenetAudio error detection and processing US 8533551 B2 Zusammenfassung A method of processing a DAB audio stream, the method comprising: receiving a compressed and modulated DAB audio stream comprising a plurality of audio frames encoded with scale factors and a DAB-CRC error detection code for indicating errors in the scale factors; demodulating the DAB stream; and processing the demodulated and still compressed DAB stream responsive to the DAB-CRC of at least one audio frame of the plurality of audio frames; by determining a trend in values of scale factors and repairing or concealing the error in the scale factor responsive to the trend.
Detection Sy Bor Wang, David Demirdjian, Hedvig Kjellstrom & Trevor Darrell What We propose a framework for communication error detection in conversational systems using audio-visual observations of users. Why Many spoken dialogue systems have difficulty detecting the occurrence of communication errors (e.g. errors made by the speech recognizer). By our definition, a communication error is when the automatic speech recognition system misinterprets the user and makes an erroneous reply. Considerable research has been invested in monitoring audio cues to detect such communication errors. Various researchers have shown that human users change their speaking style when they encounter a problem with a conversational system. For example, users tend to speak slower or louder when speech recognition errors occur. These problems motivated the monitoring of prosodic aspects of a speaker's utterances and several studies have shown that using automatically extracted prosodic features can help in communication error detection [1,2,3]. However, the performance of using prosody features differs across studies, and since human to human communication is done audio-visually in a complementary manner, this hints at the use of visual cues to improve error detection performance. Recent perceptual studies indicate that communication error detection can be improved significantly if both acoustic and visual modalities are taken into account. A study conducted in [4] explored the human perception of audio-visual cues in dialogue systems and showed that given the visual footage of the speaker, human observers performed better at recognizing communication errors than when only audio recordings were provided: speech and non-verbal/verbal facial expressions of the users were shown to be good indicators of the communication state. This insight motivates us