voice) is the target signal and the

second one (woman s voice) is the interfering speaker. To contrast the

effects of an interference speaker (non-stationary noise) with a white

noise inference (stationary noise/constant power) a white noise signal

is also used. These signals are then scaled (varying SNR) to illustrate

Good intelligibility (~.6), barely intelligible (~.2), and unintelligible

(.1).



The output of the scr ipt plots the Speech intelligibility Index for 100 ms

windows over the speech signal, and displays the computed mean and standard

deviation of SII (for active speech, silence intervals were excluded).

Users can change the envelope threshold which is used to remove the



Functions required from Array Toolbox

1. intel.m

2. spectrumlevel.m

3. sii.m

4. rmsilence.m

2 Data Files required



Written by Arulkumaran Muthukumarasamy (arulkumaran@uky.edu) July 2008-voice) is the target signal and the

　second one (woman s voice) is the interfering speaker. To contrast the

　effects of an interference speaker (non-stationary noise) with a white

　noise inference (stationary noise/constant power) a white noise signal

　is also used. These signals are then scaled (varying SNR) to illustrate

　Good intelligibility (~.6), barely intelligible (~.2), and unintelligible

　(.1).

　

　The output of the scr ipt plots the Speech intelligibility Index for 100 ms

　windows over the speech signal, and displays the computed mean and standard

　deviation of SII (for active speech, silence intervals were excluded).

　Users can change the envelope threshold which is used to remove the



　Functions required from Array Toolbox

　 1. intel.m

　 2. spectrumlevel.m

　 3. sii.m

　 4. rmsilence.m

　2 Data Files required



　Written by Arulkumaran Muthukumarasamy (arulkumaran@uky.edu) July 2008