Analogue speech signal is one of the most natural means used by humans for communication purposes. The emergence of digital modulation and coding techniques has made the transmission of analogue speech (as digital content) over various conduits possible, albeit with inevitable signal degradation as a result of errors inherent in the conversion process. A need naturally arises for determining the quality of speech received at the information sink, with a view to enhancing its robustness to degradation suffered in transit over the communication channel. We present in this paper analytic methods of qualitative assessment of the quality of recovered digitally transmitted speech. A methodology for determining the intelligibility of speech by using segmental SNR gotten by dividing the speech signal into M integer segments is proposed. This methodology has the following advantages: a) it allows for assessing the dynamics of change of speech quality in real-time through statistical modeling, b) it obviates the need for expensive, yet subjective experimental approaches like MOS, and c) it takes into consideration not only the signal power, but also its spectral characteristics which is a step above the use of Modulated Noise Reference Units (MNRUs). Using the obtained results, a procedure for analysis of speech intelligibility by means of statistical modeling is developed.
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