Incremental Processing Under Degraded Conditions: Relations to Speech Recognition in Noise and Cognition

Spectral degradation disrupts the rapid, incremental processes that support spoken word recognition, but most studies quantify endpoint accuracy rather than the time course of lexical access, and the extent to which cognitive resources compensate for this disruption remains unclear. This study examined the influence of spectral resolution and cognition on lexical access using a gated word recognition paradigm. Thirty adults with normal hearing identified monosyllabic words presented in progressively longer fragments under full-spectrum and 8-channel sine-wave vocoded conditions. Isolation points (IPs), the shortest segment required for stable identification, were measured. Speech perception was assessed using vocoded AzBio sentences in quiet and noise (+10 dB and +5 dB SNR) and vocoded Consonant-Nucleus-Consonant (CNC) words in quiet. Working memory and executive function were evaluated using the Abbreviated Reading Span Test and Trail Making Test. Full-spectrum speech supported efficient lexical access, whereas vocoded speech required nearly complete word information (62.7% vs. 98.9% of word duration), indicating severe delays in incremental processing. Near-ceiling CNC and AzBio scores in quiet did not correlate with IPs, but IPs were strongly associated with AzBio performance in noise. Cognitive measures were intercorrelated but not significantly associated with IPs or speech perception scores after correction for multiple comparisons, although the sample was powered to detect only large associations. These findings suggest that the efficiency of incremental lexical access under spectral degradation captures variability in speech-in-noise perception that is not evident in endpoint accuracy in quiet.