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. 2010 Oct;128(4):2075-84.
doi: 10.1121/1.3478845.

Relative contribution of off- and on-frequency spectral components of background noise to the masking of unprocessed and vocoded speech

Frédéric Apoux  1 , Eric W Healy
Affiliations

Relative contribution of off- and on-frequency spectral components of background noise to the masking of unprocessed and vocoded speech

Frédéric Apoux et al. J Acoust Soc Am. 2010 Oct.

Abstract

The present study examined the relative influence of the off- and on-frequency spectral components of modulated and unmodulated maskers on consonant recognition. Stimuli were divided into 30 contiguous equivalent rectangular bandwidths. The temporal fine structure (TFS) in each "target" band was either left intact or replaced with tones using vocoder processing. Recognition scores for 10, 15 and 20 target bands randomly located in frequency were obtained in quiet and in the presence of all 30 masker bands, only the off-frequency masker bands, or only the on-frequency masker bands. The amount of masking produced by the on-frequency bands was generally comparable to that produced by the broadband masker. However, the difference between these two conditions was often significant, indicating an influence of the off-frequency masker bands, likely through modulation interference or spectral restoration. Although vocoder processing systematically lead to poorer consonant recognition scores, the deficit observed in noise could often be attributed to that observed in quiet. These data indicate that (i) speech recognition is affected by the off-frequency components of the background and (ii) the nature of the target TFS does not systematically affect speech recognition in noise, especially when energetic masking and/or the number of target bands is limited.

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Figures

Figure 1
Figure 1
Schematic of the three target∕masker configurations used in the present study. The top, middle and bottom panels show examples for the broadband (BB), on-frequency (ON) and off-frequency (OFF) conditions, respectively.
Figure 2
Figure 2
Percent correct scores for consonant identification as a function of masker configuration [broadband (BB), on-frequency (ON) and off-frequency (OFF)] for the four combinations of SNR (0 and 6 dB) and masker type [speech-shaped noise (SSN) and time-reversed speech (TRS)]. The left, middle, and right panels correspond to the 10-, 15-, and 20-band conditions, respectively. In each panel, performance in quiet is indicated by a dashed line.
Figure 3
Figure 3
Percent correct scores relative to those in quiet as a function of the SNR (0 and 6 dB) and masker type [speech-shaped noise (SSN) and time-reversed speech (TRS)] combination for the three masker configurations [broadband (BB), on-frequency (ON) and off-frequency (OFF)]. The error bars show one standard deviation.
Figure 4
Figure 4
The same as Fig. 2, but for vocoded target bands.
Figure 5
Figure 5
Proportion of responses correct relative to performance in quiet as a function of the SNR (0 and 6 dB) and masker type [speech-shaped noise (SSN) and time-reversed speech (TRS)] combination. The left, middle, and right panels correspond to the 10-, 15-, and 20-band conditions, respectively. In each panel, the bars correspond to combinations of masker configuration [broadband (BB), on-frequency (ON) and off-frequency (OFF)] and speech processing [unprocessed (UNP) and vocoded (VOC)]. Asterisks indicate the UNP proportions that were significantly different from the corresponding VOC proportion. The error bars show one standard deviation.
Figure 6
Figure 6
Percent correct scores for consonant identification as a function of masker configuration [broadband (BB), on-frequency (ON) and off-frequency (OFF)] for the four combinations of masker type [speech-shaped noise (SSN) and time-reversed speech (TRS)] and masker processing [unprocessed (VOCt) and vocoded(VOCtm)]. Data were collected in the 15-band condition only. For reference, the UNP data from Fig. 2 are also shown (diamonds).
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References

    1. ANSI S3.6-2004 (2004). Specifications for Audiometers (American National Standards Institute, New York: ).
    1. Apoux, F., and Bacon, S. P. (2008a). “Selectivity of modulation interference for consonant identification in normal-hearing listeners,” J. Acoust. Soc. Am. JASMAN 123, 1665–1672.10.1121/1.2828067 - DOI - PubMed
    1. Apoux, F., and Bacon, S. P. (2008b). “Differential contribution of envelope fluctuations across frequency to consonant identification in quiet,” J. Acoust. Soc. Am. JASMAN 123, 2792–2800.10.1121/1.2897916 - DOI - PMC - PubMed
    1. Apoux, F., and Healy, E. W. (2009). “On the number of auditory filter ouputs needed to understand speech: Further evidence for auditory channel independence,” Hear. Res. HERED3 255, 99–108.10.1016/j.heares.2009.06.005 - DOI - PMC - PubMed
    1. Bacon, S. P. (1999). “Some effects of background noise on modulation detection interference,” Hear. Res. HERED3 129, 20–26.10.1016/S0378-5955(98)00215-9 - DOI - PubMed

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