Testing the ability of speech recognizers to measure the effectiveness of encoding algorithms for digital speech transmission

Modern communication channels, such as digital cellular telephony, often convey human speech in a highly encoded form. Methods that rely on human subjects to evaluate the quality of such channels are too costly to deploy on a large scale; thus, automated methods are often used to model quality as pe...

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Bibliographic Details
Published in:MILCOM 1999 Proceedings Vol. 2; pp. 1468 - 1472 vol.2
Main Authors: Chernick, C.M., Leigh, S., Mills, K.L., Toense, R.
Format: Conference Proceeding
Language:English
Published: Piscataway NJ IEEE 1999
Subjects:
Applied sciences
Automatic speech recognition
Coding, codes
Communication channels
Decoding
Encoding
Exact sciences and technology
Humans
Information, signal and communications theory
Large-scale systems
Signal and communications theory
Signal processing
Signal to noise ratio
Speech analysis
Speech processing
Speech recognition
Telecommunications and information theory
Telecommunications: signal transmission and processing; communication satellites
Testing
Coding
Cellular material
Measurement method
Experimental study
Speech transmission
Algorithm
Digital transmission
Signal to noise ratio
ISBN:9780780355385, 0780355385
Online Access:Get full text
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Summary:Modern communication channels, such as digital cellular telephony, often convey human speech in a highly encoded form. Methods that rely on human subjects to evaluate the quality of such channels are too costly to deploy on a large scale; thus, automated methods are often used to model quality as perceived by humans. Traditional automated methods that use signal to noise ratios (SNR) to judge the quality of channels do not model human perception well when applied to highly encoded speech. For this reason, researchers investigate alternative means to objectively measure the quality of such channels. We explore the feasibility and applicability of using automated speech recognition technology to model human perception of the quality of communication channels that carry highly encoded (compressed) human speech.
ISBN:9780780355385
0780355385
DOI:10.1109/MILCOM.1999.821447