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Comparison of DPCM and Subband Codec performance in the presence of burst errors

This thesis is a preliminary study of the relative performance of the major speech
compression techniques, Differential Pulse Code Modulation (DPCM) and Subband
Coding (SBC) in the presence of transmission distortion. The combined effect of the
channel distortions and the channel codec including error correction is represented by
bursts of bit errors. While compression is critical since bandwidth is scarce in a wireless
channel, channel distortions are greater and less predictable. Little to no work has
addressed the impact of channel errors on perceptual quality of speech due to the
complexity of the problem. At the transmitter, the input signal is compressed to 24 kbps
using either DPCM or SBC, quantized, binary encoded and transmitted over the burst
error channel. The reverse process is carried out at the receiver. DPCM achieves
compression by removing redundant information in successive time domain samples,
while SBC uses lower resolution quantizer to encode frequency bands of lower
perceptual importance. The performance of these codecs is evaluated for BERs of 0.001
and 0.05, with the burst lengths varying between 4 and 64 bits. Two different speech
segments - one voiced and one unvoiced are used in testing. Performance measures
include two objective tests signal to noise ratio (SNR) & segmental SNR, and a
subjective test of perceptual quality - the Mean Opinion Score (MOS). The results
obtained show that with a fixed BER and increasing burst length in bits, the total errors
reduce in the decoded speech thereby improving its perceptual quality for both DPCM
and SBC. Informal subjective tests also demonstrate this trend as well as indicate
distortion in DPCM seemed to be less perceptually degrading than SBC. / Graduation date: 1999

Identiferoai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33508
Date31 August 1998
CreatorsBhutani, Meeta
ContributorsStonick, Virginia L.
Source SetsOregon State University
Languageen_US
Detected LanguageEnglish
TypeThesis/Dissertation

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