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6- Speech Quality Assessment

6- Speech Quality Assessment. Quality Levels Subjective Tests Objective Tests Signal To Noise Ratio(SNR) Segmental SNR. Quality Levels. Synthetic Quality (Under 4.8 kbps) Communication Quality (4.8 to 13 kbps) Toll Quality (13 to 64 kbps) Broadcast Quality (Upper 64 kbps). Test Types.

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6- Speech Quality Assessment

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  1. 6-Speech Quality Assessment • Quality Levels • Subjective Tests • Objective Tests • Signal To Noise Ratio(SNR) • Segmental SNR

  2. Quality Levels • Synthetic Quality (Under 4.8 kbps) • Communication Quality (4.8 to 13 kbps) • Toll Quality (13 to 64 kbps) • Broadcast Quality (Upper 64 kbps)

  3. Test Types • Intelligibility • Naturalness • Subjective (Test by user) • Objective (Test by system)

  4. First ClassSubjective Intelligibility Tests • Diagnostic Rhyme Test (DRT) • Selecting between two CVC by different first C • First C should have specific properties • Ex. hop - fop And than - dan • Modified Rhyme Test (MRT) • Selecting between CVC’s by different first C • Ex. Cat, bat, rat, mat, fat, sat

  5. First Class (Cont’d)Subjective Intelligibility tests • DRT is very applicable and credible • In this test user can hear the speech only once

  6. Second ClassSubjective Naturalness tests • Mean Opinion Score (MOS) • MOS is very applicable and credible • In this test user can hear the speech a lot • Diagnostic Acceptability Measure (DAM) • This test is very complex

  7. Mean Opinion Score (MOS) • Scores for MOS are like this Score Speech Quality 1 2 3 4 5 Not Acceptable Weak Medium Good Excellent

  8. Diagnostic Acceptability Measure (DAM) • This test is very complex • In this test there is 19 different parameters for score. These parameters divide into 3 main groups: • Signal Quality • Background Quality • Total Quality

  9. Objective Tests • These tests can not be used for intelligibility. Because system couldn’t recognize speech intelligibility • Objective tests can only be used for speech Naturalness

  10. Objective Tests (Cont’d) • Articulation Index (AI) • Signal to Noise Ratio (SNR) • Global (Classic) SNR • Segmental SNR • Frequency Weighted Segmental SNR

  11. Articulation Index (AI) • AI assumes that different frequency bands distortion are independent, and measure signal quality in different bands. • In each band determines percentage of perceptible signal by listener 20 Bands HZ . . . . . . . . . 200 6100

  12. Articulation index (Cont’d) • Perceptible by user signal : • 1- Upper the human hearing threshold • 2- Under the human pain threshold • 3- Upper the Masking Noise level • In each case one of the states 1 or 3 is prevail

  13. Articulation index (Cont’d) • In AI SNR measured isolated in each band

  14. Signal To Noise Ratio(SNR)

  15. Segmental SNR j’th Frame SNR M : Number of frames

  16. Frequency Weighted Segmental SNR K : Number of frequency bands M : Number of frames

  17. Itakura Measure Is the envelope spectrum Use from All-Pole (AR) Model

  18. Itakura Measure (Cont’d) This is based on the spectrum difference between main signal and assessment signal Autoregressive Coefficients Reflection Coefficients Autocorrelation Coefficients

  19. Itakura Measure (Cont’d) m :Index of frame l : Number of coefficients

  20. Itakura Measure (Cont’d) Is the l’th parameter of the frame that conduces m’th sample

  21. Weighted Spectral Slope Measure(WSSM) Is STFT of k’th band of the frame that conduces m’th sample

  22. 7-Speech Recognition • Speech Recognition Concepts • Speech Recognition Approaches • Recognition Theories • Bayse Rule • Simple Language Model • P(A|W) Network Types

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