Release from informational masking by time reversal of native and non-native interfering speech

In many studies, the influence of intelligibility of the interfering speech is avoided by reversing it in time. Usually, intelligibility with time-reversed interfering speech indeed is higher compared to that with normal interfering speech. However, due to the nature of speech, reversed speech also gives rise to increased forward masking. The latter will result in a decrease in intelligibility. Thus, differences in intelligibility as a consequence of reversing speech in time are due to two opposite effects. This paper describes a speech reception threshold (SRT) test with intelligible and unintelligible interfering speech played normally and time-reversed. With Dutch listeners, Swedish reversed interfering speech gave a rise in SRT of 2.3 dB compared with the Swedish interfering speech (played normally). The difference can be attributed to differences in forward masking. Dutch time-reversed interfering speech gave a decrease in SRT of 4.3 dB compared to (intelligible) Dutch interfering speech. The latter is the result of both a release from informational masking and an increase in forward masking. Therefore, the amount of informational masking is larger than 4.3 dB and, if one assumes similar differences in forward masking for Dutch and Swedish speech, may amount to 6.6 d

Modeling speech intelligibility in quiet and noise in listeners with normal and impaired hearing

The speech intelligibility index (SII) is an often used calculation method for estimating the proportion of audible speech in noise. For speech reception thresholds (SRTs), measured in normally hearing listeners using various types of stationary noise, this model predicts a fairly constant speech proportion of about 0.33, necessary for Dutch sentence intelligibility. However, when the SII model is applied for SRTs in quiet, the estimated speech proportions are often higher, and show a larger inter-subject variability, than found for speech in noise near normal speech levels [65 dB sound pressure level (SPL)]. The present model attempts to alleviate this problem by including cochlear compression. It is based on a loudness model for normally hearing and hearing-impaired listeners of Moore and Glasberg [(2004). Hear. Res. 188, 70-88]. It estimates internal excitation levels for speech and noise and then calculates the proportion of speech above noise and threshold using similar spectral weighting as used in the SII. The present model and the standard SII were used to predict SII values in quiet and in stationary noise for normally hearing and hearing-impaired listeners. The present model predicted SIIs for three listener types (normal hearing, noise-induced, and age-induced hearing loss) with markedly less variability than the standard SI

Modelling the speech reception threshold in non-stationary noise in hearing-impaired listeners as a function of level

The extended speech intelligibility index (ESII) model (Rhebergen et al, 2006) forms an upgrade to the conventional speech intelligibility index model. For normal-hearing listeners the ESII model is able to predict the speech reception threshold (SRT) in both stationary and non-stationary noise maskers. In this paper, a first attempt is made to evaluate the ESII with SRT data obtained by de Laat and Plomp (1983), and Versfeld and Dreschler (2002) of hearing-impaired listeners in stationary, 10-Hz interrupted, and non-stationary speech-shaped noise measured at different noise levels. The results show that the ESII model is able to describe the SRT in different non-stationary noises for normal-hearing listeners at different noise levels reasonably well. However, the ESII model is less successful in the case of predicting the SRT in non-stationary noise for hearing-impaired subjects. As long as the present audibility models cannot describe the auditory processing in a listener with cochlear hearing loss accurately, it is difficult to distinguish between raised SRTs due to supra-threshold deficits or factors such as cognition, age, and language skill

Relationship between speech recognition in noise and sparseness

Established methods for predicting speech recognition in noise require knowledge of clean speech signals, placing limitations on their application. The study evaluates an alternative approach based on characteristics of noisy speech, specifically its sparseness as represented by the statistic kurtosis. Design: Experiments 1 and 2 involved acoustic analysis of vowel-consonant-vowel (VCV) syllables in babble noise, comparing kurtosis, glimpsing areas, and extended speech intelligibility index (ESII) of noisy speech signals with one another and with pre-existing speech recognition scores. Experiment 3 manipulated kurtosis of VCV syllables and investigated effects on speech recognition scores in normal-hearing listeners. Study sample: Pre-existing speech recognition data for Experiments 1 and 2; seven normal-hearing participants for Experiment 3. Results: Experiments 1 and 2 demonstrated that kurtosis calculated in the time-domain from noisy speech is highly correlated (r &gt; 0.98) with established prediction models: glimpsing and ESII. All three measures predicted speech recognition scores well. The final experiment showed a clear monotonic relationship between speech recognition scores and kurtosis. Conclusions: Speech recognition performance in noise is closely related to the sparseness (kurtosis) of the noisy speech signal, at least for the types of speech and noise used here and for listeners with normal hearing<br/