week8_objective measurements of speech intelligibility

8/7/2019 Week8_Objective Measurements of Speech Intelligibility

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Measurements of Audio Systems

Week 8


2/24

Brief Introduction to Correct Gain

Structure


3/24

Two approaches (or three)


4/24

Measurements of Audio Systems in

Space

Some measurements developed for architecturalacoustics can be used to measure audio systems whenmeasuring the response of a system in a space.

And thats what this lecture/demonstration is about.

For small signal measurements refer to Metzlers book.


5/24

Reverberation Time and Other Decay

Parameters

R60

T10

T20 T30


6/24

Clarity C50 or C80

Measurement of first 50ms

compared to the rest of the

reverberant tail.


7/24

Two main methods for evaluation of

audio systems

Dual FFT

Impulse Response Measurements


8/24

Objective Measurements of

Speech Intelligibility

Week 8


9/24

Warning

Good speech intelligibility is not the only factor

governing perceived quality in audio systems.

A good example is the high output horns at train

stations. Speech is highly intelligible but they do

not sound as a high quality audio system (to the

normal population at least).


10/24

Factors affecting speech intelligibility

Bandwidth

Frequency response

Reverberation time Level

Signal to Noise Ratio

Directivity of the loudspeaker


11/24

Objective Measurements of Speech

Intelligibility

Articulation Index

%Alcons

Direct to reverberant ratios (C50, C80) STI


12/24

Articulation Index (AI)

Articulation Index is the simplest predictor of

speech intelligibility. Works for very simple

systems (e.g. telephones, radios, etc).

Calculates ratio of interfering noise spectrum

and desired noise spectrum.

Standardized in ANSI S3.5 1997.

Not suitable for complex systems (such as

loudspeaker systems in auditoria).


13/24

Direct to Reverberant Ratios

Simple to derive from impulse response

measurements.

Widely used in auditorium acoustics.

C50 has been found to be a good predictor for

speech intelligibility.

Desired values above +4dB for good

intelligibility.


14/24

%Alcons (Articulation loss of

consonants)

Method developed in the 70s by Peutz and then

refined in the 80s.

Takes into account background noise, direct sound

level, reverberant sound level and reverberationtime.

Expressed in percentage of consonants not

understood, therefore a low number is desirable.Only takes into account the 1/3 octave band

centered at 2kHz.


15/24

STI (Speech Transmission Index)

Method developed in the 70s by Houtgast andSteeneken and continually refined.

Most widely used and reliable method for

calculation of speech intelligibility.Standardized in IEC 60268-16 Sound systemequipment Part 16: Objective rating of speechintelligibility by speech transmission index.

Based on MTF (modulation transfer function).

Takes into account masking of adjacent bands.


16/24

MTF


17/24

MTF theoretical expression


18/24

MTF to SNR

The MTF is transformed into an apparent SNR by

transforming it into a logarithmic expression.

SNRApp=10lg(m(F)/1-m(F))


19/24

SNR to transmission index


20/24

Calculation Matrix

Calculations of MTF are done for 14 modulation

frequencies (0.63, 0.8, 1, 1.25, 1.6, 2, 2.5, 3.15,

4, 5, 6.3, 8, 10 and 12.5 Hz) and 7 frequency

bands (125, 250, 500, 1k, 2k, 4k and 8k Hz).

Results in a matrix of 98 values.


21/24

Modeling of Masking

Masking is taken into account by contributing to

the noise of adjacent bands. Masking effects are

modeled as noise with a masking slope of -35dB

in the band immediately above.


22/24

Weighting Factors

The final STI value is calculated by applying a

weighting factor to each measurement.

The weighting factors take into account the

hearing threshold.

There are different weighting factors that can be

applied to predict the STI of female and male

speakers.


23/24

Other methods

RASTI and STITEL were developed when

computational times were higher. They take into

account less modulation frequencies and

frequency bands.


24/24

Some criticism on STI

STIs means to take into account masking is very

coarse.

It has been found that this can be improved by

utilizing psychoacoustic models that take into

account forward masking and a finer frequency

resolution.

week8_objective measurements of speech intelligibility

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