This paper describes a new artificial speech signal (ASVQ Artificial Speech by Vector Quantization technique) which reflects the average characteristics of the human voice. The ASVQ is intended for use as a test signal in the objective evaluation of speech coding system quality.To obtain the average characteristics, a very large speech data base is analyzed. The ASVQ generation method which reflects the extracted average characteristics of the human voice is formulated. This method applies vector quantizing analysis to the speech data base. The LPC speech synthesis circuit is used to reproduce the average characteristics. Finally, the new artificial speech signal is compared with a human voice and the estimation accuracy of the subjective quality of speech coding systems and nonlinear distortions is evaluated.
Although there has been some research on the relation between random errors that cause speech quality impairment and mean opinion score (MOS), speech quality impairment factors have not been clarified for the bursty code error noise. A subjective evaluation experiment that uses a free conversational form is conducted and the effect of bursty code error noise on speech quality is studied. Moreover, Q-value quantification of bursty code error noise and random code error noise and its additivity are studied. MOS and tolerance rate change linearly according to a logarithmic number of bursts during a certain length of conversation. Impairment changes according to the number of error bit rates in a random bit error. A more simplified relationship can be obtained by converting MOSS to Q values. It is confirmed that the additivity law holds between Q values for impairment that is due to random and bursty errors.Key words: Transmission quality impairment; speech transmission; burst bit error; mean opinion score; ransom error.The goals of this research are to clarify the effect of burst code error noise, or simply "burst error noise, " on speech quality, and to study (1) the relation between the statistical properties of burst error noise and quality impairment, (2) the tolerance limit of quality impairment, and (3) the additivity law between Q values for the impairment due to random and burst errors. $,+,= --log,,(lO-"%+ 10 1 0 -4 ) m 8
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