文件名称:testscript_intel
- 所属分类：
- 单片机(51,AVR,MSP430等)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2012-11-26
- 文件大小：
- 2kb
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- tun****
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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
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
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testscript_intel.m