The human voice is a highly flexible instrument for self-expression, yet voice identity perception is largely studied using controlled speech recordings. Using two voice-sorting tasks with naturally varying stimuli, we compared the performance of listeners who were familiar and unfamiliar with the TV show Breaking Bad. Listeners organised audio clips of speech with (1) low-expressiveness and (2) high-expressiveness into perceived identities. We predicted that increased expressiveness (e.g., shouting, strained voice) would significantly impair performance. Overall, while unfamiliar listeners were less able to generalise identity across exemplars, the two groups performed equivalently well when telling voices apart when dealing with low-expressiveness stimuli. However, high vocal expressiveness significantly impaired telling apart in both the groups: this led to increased misidentifications, where sounds from one character were assigned to the other. These misidentifications were highly consistent for familiar listeners but less consistent for unfamiliar listeners. Our data suggest that vocal flexibility has powerful effects on identity perception, where changes in the acoustic properties of vocal signals introduced by expressiveness lead to effects apparent in familiar and unfamiliar listeners alike. At the same time, expressiveness appears to have affected other aspects of voice identity processing selectively in one listener group but not the other, thus revealing complex interactions of stimulus properties and listener characteristics (i.e., familiarity) in identity processing.

Dengue virus (DENV) is the leading cause of arboviral diseases in humans worldwide. The envelope (E) protein of DENV is the major target of neutralizing antibodies (Abs). Previous studies have shown that a significant proportion of anti-E Abs in human serum after DENV infection recognize the highly conserved fusion loop (FL) of E protein. The role of anti-FL Abs in protection against subsequent DENV infection versus pathogenesis remains unclear. A human anti-E monoclonal Ab was used as a standard in a virion-capture ELISA to measure the concentration of anti-E Abs, [anti-E Abs], in dengue-immune sera from Nicaraguan patients collected 3, 6, 12 and 18 months post-infection. The proportion of anti-FL Abs was determined by capture ELISA using virus-like particles containing mutations in FL, and the concentration of anti-FL Abs, [anti-FL Abs], was calculated. Neutralization titers (NT50) were determined using a previously described flow cytometry-based assay. Analysis of sequential samples from 10 dengue patients revealed [anti-E Abs] and [anti-FL Abs] were higher in secondary than in primary DENV infections. While [anti-FL Abs] did not correlate with NT50 against the current infecting serotype, it correlated with NT50 against the serotypes to which patients had likely not yet been exposed (“non-exposed” serotypes) in 14 secondary DENV3 and 15 secondary DENV2 cases. These findings demonstrate the kinetics of anti-FL Abs and provide evidence that anti-FL Abs play a protective role against “non-exposed” serotypes after secondary DENV infection.

Inhibition—the ability to suppress goal-irrelevant information—is thought to be an important cognitive skill in many situations, including speech-in-noise (SiN) perception. One way to measure inhibition is by means of Stroop tasks, in which one stimulus dimension must be named while a second, more prepotent dimension is ignored. The to-be-ignored dimension may be relevant or irrelevant to the target dimension, and the inhibition measure—Stroop interference (SI)—is calculated as the reaction time difference between the relevant and irrelevant conditions. Both SiN perception and inhibition are suggested to worsen with age, yet attempts to connect age-related declines in these two abilities have produced mixed results. We suggest that the inconsistencies between studies may be due to methodological issues surrounding the use of Stroop tasks. First, the relationship between SI and SiN perception may differ depending on the modality of the Stroop task; second, the traditional SI measure may not account for generalized slowing or sensory declines, and thus may not provide a pure interference measure. We investigated both claims in a group of 50 older adults, who performed two Stroop tasks (visual and auditory) and two SiN perception tasks. For each Stroop task, we calculated interference scores using both the traditional difference measure and methods designed to address its various problems, and compared the ability of these different scoring methods to predict SiN performance, alone and in combination with hearing sensitivity. Results from the two Stroop tasks were uncorrelated and had different relationships to SiN perception. Changing the scoring method altered the nature of the predictive relationship between Stroop scores and SiN perception, which was additionally influenced by hearing sensitivity. These findings raise questions about the extent to which different Stroop tasks and/or scoring methods measure the same aspect of cognition. They also highlight the importance of considering additional variables such as hearing ability when analyzing cognitive variables.

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The effects of high variability training during voice identity learning 2 High variability training has been shown to benefit the learning of new face identities. In three experiments, we investigated whether this is also the case for voice identity learning. In Experiment 1a, we contrasted high variability training setswhich included stimuli extracted from a number of different recording sessions, speaking environments and speaking stylewith low variability stimulus sets that only included a single speaking style (read speech) extracted from one recording session (see Ritchie & Burton, 2017 for faces). Listeners were tested on an old/new recognition task using read sentences (i.e. test materials fully overlapped with the low variability training stimuli) and we found a high variability disadvantage. In Experiment 1b, listeners were trained in a similar way, however, now there was no overlap in speaking style or recording session between training sets and test stimuli. Here, we found a high variability advantage. In Experiment 2, variability was manipulated in terms of the number of unique items as opposed to number of unique speaking styles. Here, we contrasted the high variability training sets used in Experiment 1a with low variability training sets that included the same breadth of styles, but fewer unique items; instead, individual items were repeated (see Murphy, Ipser, Gaigg & Cook, 2015 for faces). We found only weak evidence for a high variability advantage, which could be explained by stimulus-specific effects. We propose that high variability advantages may be particularly pronounced when listeners are required to generalise from trained stimuli to different-sounding, previously unheard stimuli. We discuss these findings in the context of mechanisms thought to underpin advantages for high variability training.

Information associated with the self is prioritized relative to information associated with others and is therefore processed more quickly and accurately. Across three experiments, we examined whether a new externally-generated voice could become associated with the self and thus be prioritized in perception. In the first experiment, participants learned associations between three unfamiliar voices and three identities (self, friend, stranger). Participants then made speeded judgements of whether voiceidentity pairs were correctly matched, or not. A clear self-prioritization effect was found, with participants showing quicker and more accurate responses to the newly selfassociated voice relative to either the friend-or stranger-voice. In two further experiments, we tested whether this prioritization effect increased if the self-voice was gender-matched to the identity of the participant (Experiment 2) or if the self-voice was chosen by the participant (Experiment 3). Gender-matching did not significantly influence prioritization; the self-voice was similarly prioritized when it matched the gender identity of the listener as when it did not. However, we observed that choosing the self-voice did interact with prioritization (Experiment 3); the self-voice became more prominent, via lesser prioritization of the other identities, when the self-voice was chosen relative to when it was not. Our findings have implications for the design and selection of individuated synthetic voices used for assistive communication devices, suggesting that agency in choosing a new vocal identity may modulate the distinctiveness of that voice relative to others.Voice is central to the dynamic construction of the self and is therefore of great personal and social importance. A speaker's unique voice pattern conveys a wealth of information about their physical self to a listener, including their age, gender, health, and affective state (Kreiman & Sidtis, 2011). A speaker also has extensive control over the dynamic use of their vocal apparatus and is able to flexibly and deliberately modulate the acoustics of their voice (Hughes, Mogilski, & Harrison, 2014;McGettigan et al., 2013;McGettigan & Scott, 2014) to fulfil diverse communicative goals according to changes in social demands and the acoustic environment.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Models of voice perception propose that identities are encoded relative to an abstracted average or prototype. While there is some evidence for norm-based coding when learning to discriminate different voices, little is known about how the representation of an individual's voice identity is formed through variable exposure to that voice. In two experiments, we show evidence that participants form abstracted representations of individual voice identities based on averages, despite having never been exposed to these averages during learning. We created 3 perceptually distinct voice identities, fully controlling their within-person variability. Listeners first learned to recognise these identities based on ring-shaped distributions located around the perimeter of within-person voice spaces – crucially, these distributions were missing their centres. At test, listeners’ accuracy for old/new judgements was higher for stimuli located on an untrained distribution nested around the centre of each ring-shaped distribution compared to stimuli on the trained ring-shaped distribution.