Multiple sources of acoustic variation affect speech processing efficiency.

Phonetic variability across talkers imposes additional processing costs during speech perception, evident in performance decrements when listening to speech from multiple talkers. However, within-talker phonetic variation is a less well-understood source of variability in speech, and it is unknown how processing costs from within-talker variation compare to those from between-talker variation. Here, listeners performed a speeded word identification task in which three dimensions of variability were factorially manipulated: between-talker variability (single vs multiple talkers), within-talker variability (single vs multiple acoustically distinct recordings per word), and word-choice variability (two- vs six-word choices). All three sources of variability led to reduced speech processing efficiency. Between-talker variability affected both word-identification accuracy and response time, but within-talker variability affected only response time. Furthermore, between-talker variability, but not within-talker variability, had a greater impact when the target phonological contrasts were more similar. Together, these results suggest that natural between- and within-talker variability reflect two distinct magnitudes of common acoustic-phonetic variability: Both affect speech processing efficiency, but they appear to have qualitatively and quantitatively unique effects due to differences in their potential to obscure acoustic-phonemic correspondences across utterances.

Selecting among competing models of talker adaptation: Attention, cognition, and memory in speech processing efficiency.

Phonetic variability across talkers imposes additional processing costs during speech perception, often measured by performance decrements between single- and mixed-talker conditions. However, models differ in their predictions about whether accommodating greater phonetic variability (i.e., more talkers) imposes greater processing costs. We measured speech processing efficiency in a speeded word identification task, in which we manipulated the number of talkers (1, 2, 4, 8, or 16) listeners heard. Word identification was less efficient in every mixed-talker condition compared to the single-talker condition, but the magnitude of this performance decrement was not affected by the number of talkers. Furthermore, in a condition with uniform transition probabilities between two talkers, word identification was more efficient when the talker was the same as the prior trial compared to trials when the talker switched. These results support an auditory streaming model of talker adaptation, where processing costs associated with changing talkers result from attentional reorientation.