Auditory and language contributions to neural encoding of speech features in noisy environments

Abstract

Recognizing speech in noisy environments is a challenging task that involves both auditory and language mechanisms. Previous studies have demonstrated human auditory cortex can reliably track the temporal envelope of speech in noisy environments, which provides a plausible neural basis for noise-robust speech recognition. The current study aimed at teasing apart auditory and language contributions to noise-robust envelope tracking by comparing the neural responses of 2 groups of listeners, i.e., native listeners and foreign listeners who did not understand the testing language. In the experiment, speech signals were mixed with spectrally matched stationary noise at 4 intensity levels and listeners’ neural responses were recorded using electroencephalography (EEG). When the noise intensity increased, the neural response gain increased in both groups of listeners, demonstrating auditory gain control. Language comprehension generally reduced the response gain and envelope-tracking precision, and modulated the spatial and temporal profile of envelope-tracking activity. Based on the spatio-temporal dynamics of envelope-tracking activity, a linear classifier can jointly decode the 2 listener groups and 4 levels of noise intensity. Altogether, the results showed that without feedback from language processing, auditory mechanisms such as gain control can lead to a noise-robust speech representation. High-level language processing modulated the spatio-temporal profile of the neural representation of speech envelope, instead of generally enhancing the envelope representation.