Spatial efficiency of blind source separation based on decorrelation – subjective and objective assessment
► Different angular target-masker configurations. ► Speech masked by babble noise and recorded by dummy head. ► Subjective vs. objective measure for evaluation of speech enhancement algorithm. ► Subjective and objective measure give different values. ► High spatial efficiency of BSS was proven in bo...
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| Published in | Speech communication Vol. 53; no. 3; pp. 390 - 402 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.03.2011
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0167-6393 1872-7182 |
| DOI | 10.1016/j.specom.2010.11.002 |
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| Abstract | ► Different angular target-masker configurations. ► Speech masked by babble noise and recorded by dummy head. ► Subjective vs. objective measure for evaluation of speech enhancement algorithm. ► Subjective and objective measure give different values. ► High spatial efficiency of BSS was proven in both measures.
Blind source separation (BSS) method is one of the newest multisensorial methods that exploits statistical properties of simultaneously recorded independent signals to separate them out. The objective of this method is similar to that of beamforming, namely a set of spatial filters that separate source signals are calculated. Thus, it seems to be reasonable to investigate the spatial efficiency of BSS that is reported in this study. A dummy head with two microphones was used to record two signals in an anechoic chamber: target speech and babble noise in different spatial configurations. Then the speech reception thresholds (SRTs, i.e. signal-to-noise ratio, SNR yielding 50% speech intelligibility) before and after BSS algorithm (
Parra and Spence, 2000) were determined for audiologically normal subjects. A significant speech intelligibility improvement was noticed after the BSS was applied. This happened in most cases when the target and masker sources were spatially separated. Moreover, the comparison of objective (SNR enhancement) and subjective (intelligibility improvement) assessment methods is reported here. It must be emphasized that these measures give different results. |
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| AbstractList | ► Different angular target-masker configurations. ► Speech masked by babble noise and recorded by dummy head. ► Subjective vs. objective measure for evaluation of speech enhancement algorithm. ► Subjective and objective measure give different values. ► High spatial efficiency of BSS was proven in both measures.
Blind source separation (BSS) method is one of the newest multisensorial methods that exploits statistical properties of simultaneously recorded independent signals to separate them out. The objective of this method is similar to that of beamforming, namely a set of spatial filters that separate source signals are calculated. Thus, it seems to be reasonable to investigate the spatial efficiency of BSS that is reported in this study. A dummy head with two microphones was used to record two signals in an anechoic chamber: target speech and babble noise in different spatial configurations. Then the speech reception thresholds (SRTs, i.e. signal-to-noise ratio, SNR yielding 50% speech intelligibility) before and after BSS algorithm (
Parra and Spence, 2000) were determined for audiologically normal subjects. A significant speech intelligibility improvement was noticed after the BSS was applied. This happened in most cases when the target and masker sources were spatially separated. Moreover, the comparison of objective (SNR enhancement) and subjective (intelligibility improvement) assessment methods is reported here. It must be emphasized that these measures give different results. Blind source separation (BSS) method is one of the newest multisensorial methods that exploits statistical properties of simultaneously recorded independent signals to separate them out. The objective of this method is similar to that of beamforming, namely a set of spatial filters that separate source signals are calculated. Thus, it seems to be reasonable to investigate the spatial efficiency of BSS that is reported in this study. A dummy head with two microphones was used to record two signals in an anechoic chamber: target speech and babble noise in different spatial configurations. Then the speech reception thresholds (SRTs, i.e. signal-to-noise ratio, SNR yielding 50% speech intelligibility) before and after BSS algorithm (Parra and Spence, 2000) were determined for audiologically normal subjects. A significant speech intelligibility improvement was noticed after the BSS was applied. This happened in most cases when the target and masker sources were spatially separated. Moreover, the comparison of objective (SNR enhancement) and subjective (intelligibility improvement) assessment methods is reported here. It must be emphasized that these measures give different results. [Copyright Elsevier B.V.] Blind source separation (BSS) method is one of the newest multisensorial methods that exploits statistical properties of simultaneously recorded independent signals to separate them out. The objective of this method is similar to that of beamforming, namely a set of spatial filters that separate source signals are calculated. Thus, it seems to be reasonable to investigate the spatial efficiency of BSS that is reported in this study. A dummy head with two microphones was used to record two signals in an anechoic chamber: target speech and babble noise in different spatial configurations. Then the speech reception thresholds (SRTs, i.e. signal-to-noise ratio, SNR yielding 50% speech intelligibility) before and after BSS algorithm (Parra and Spence, 2000) were determined for audiologically normal subjects. A significant speech intelligibility improvement was noticed after the BSS was applied. This happened in most cases when the target and masker sources were spatially separated. Moreover, the comparison of objective (SNR enhancement) and subjective (intelligibility improvement) assessment methods is reported here. It must be emphasized that these measures give different results. |
| Author | Kocinski, Jedrzej Libiszewski, Pawel Sek, Aleksander |
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| Keywords | Speech enhancement Beamforming Blind source separation Speech intelligibility Performance evaluation Speech analysis Microphone Source separation Noise reduction Signal estimation Verbal perception Algorithm Anechoic room Subjective evaluation Beam forming Signal processing Test method Spatial filters Decorrelation Speech processing Signal to noise ratio |
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| Snippet | ► Different angular target-masker configurations. ► Speech masked by babble noise and recorded by dummy head. ► Subjective vs. objective measure for evaluation... Blind source separation (BSS) method is one of the newest multisensorial methods that exploits statistical properties of simultaneously recorded independent... |
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| SubjectTerms | Algorithms Applied sciences Assessments Beamforming Blind source separation Blinds Computational efficiency Detection, estimation, filtering, equalization, prediction Exact sciences and technology Information, signal and communications theory Intelligibility Mathematical analysis Miscellaneous Separation Signal and communications theory Signal processing Signal to noise ratio Signal, noise Source Separation Speech Speech Enhancement Speech intelligibility Speech processing Speech Reception Thresholds Telecommunications and information theory |
| Title | Spatial efficiency of blind source separation based on decorrelation – subjective and objective assessment |
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