1 6-Speech Quality Assessment Quality Levels IntelligibilityNaturalness Subjective Tests Objective Tests

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 than 64 kbps)

3 Test Types IntelligibilityNaturalness Subjective (Test by user) Objective (Test by system)

4 First Class Subjective 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 Class Subjective 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 ScoreSpeech Quality 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 Bands HZ

12 Articulation index (Cont’d) Perceptible by user signal : –1- Upper than human hearing threshold –2- Lower than human pain threshold –3- Upper than 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