7-Speech Quality Assessment Quality Levels Subjective Tests Objective Tests IntelligibilityNaturalness

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)

Test Types IntelligibilityNaturalness Subjective DRT, MRT MOS, DAM ObjectiveNone. Future ASR systems AI, Global SNR, Seg. SNR, FW-Seg. SNR, Itakura Measure, WSSM

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

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

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

Mean Opinion Score (MOS) Scores for MOS are like this ScoreSpeech Quality Not Acceptable Weak Medium Good Excellent

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

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

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

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

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

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

Signal To Noise Ratio(SNR)

Segmental SNR j’th Frame SNR N : Number of frames M: Frame length Usually averaged over “good frames” “good frames”: having SNRs of higher than -10dB and Saturated at +30dB

Frequency Weighted Segmental SNR F : Number of frequency bands N : Number of frames Siemens Formula:

Frequency Weighted Segmental SNR Deller Formula

Frequency Weighted Segmental SNR Other Formulas:

The Final Formula The right formula for fw-seg SNR is thus:

The Final Formula Where –M is the number of frames –j is the frame index –k is the frequency band index –w is the weight of the kth band of the jth frame –w j,k is the weight of the kth band of the jth frame –E s,k and E e,k are the energies of the kth band of signal and noise respectively

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

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

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

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

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