Perception error variation in masking contexts

Abstract

Masking noise is an important tool in speech and hearing experiments. It provides a means to simulate real world conditions and provide misperceptions that are as naturally elicited as possible. However, the exact characteristics of the variable approach to this parameter is poorly understood. The present investigation explores the types and variability of errors across different noise conditions. The English Consistent Confusion Corpus [Marxer et al., JASA 140, EL458–EL463 (2016)], which provides data on consistently reproducible mispercepts, was used for this investigation. The dataset contains tokens of words in multiple masking conditions: speech shaped noise; three talker babble modulated noise; and four-talker natural babble, correlated with signal to noise ratios that bias a listener towards a specific mispercept. This dataset contains 3200 individual word tokens from four different speakers with 15 listeners. The interaction between types and variability of misperception with the different types of masking noise is explored. As well, the suitability of the different noise conditions for speech perception experiments is discussed.