Let's all speak together! Exploring the masking effects of various languages on spoken word identification in multi-linguistic babble.

International audienceThis study aimed to characterize the linguistic interference that occurs during speech-in-speech comprehension by combining offline and online measures, which included an intelligibility task (at a -5 dB Signal-to-Noise Ratio) and 2 lexical decision tasks (at a -5 dB and 0 dB SNR) that were performed with French spoken target words. In these 3 experiments we always compared the masking effects of speech backgrounds (i.e., 4-talker babble) that were produced in the same language as the target language (i.e., French) or in unknown foreign languages (i.e., Irish and Italian) to the masking effects of corresponding non-speech backgrounds (i.e., speech-derived fluctuating noise). The fluctuating noise contained similar spectro-temporal information as babble but lacked linguistic information. At -5 dB SNR, both tasks revealed significantly divergent results between the unknown languages (i.e., Irish and Italian) with Italian and French hindering French target word identification to a similar extent, whereas Irish led to significantly better performances on these tasks. By comparing the performances obtained with speech and fluctuating noise backgrounds, we were able to evaluate the effect of each language. The intelligibility task showed a significant difference between babble and fluctuating noise for French, Irish and Italian, suggesting acoustic and linguistic effects for each language. However, the lexical decision task, which reduces the effect of post-lexical interference, appeared to be more accurate, as it only revealed a linguistic effect for French. Thus, although French and Italian had equivalent masking effects on French word identification, the nature of their interference was different. This finding suggests that the differences observed between the masking effects of Italian and Irish can be explained at an acoustic level but not at a linguistic level