talker identification
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2021 ◽  
Author(s):  
Adriel John Orena ◽  
Sarah Elizabeth Margaret Colby

Objective: Some cochlear implant (CI) users report having difficulty accessing indexical information in the speech signal, presumably due to the transformation from acoustic to electric signal in CI devices. The purpose of this paper was to systematically review and evaluate the existing research on talker perception in CI users. Specifically, we reviewed the performance of CI users in talker discrimination, gender identification, and talker recognition tasks in relation to performance by normal-hearing (NH) listeners. We also examined the different factors (such asparticipant, hearing and device characteristics) that might influence talker perception.Design: We completed a systematic search of the literature with select keywords using citation aggregation software to search Google Scholar. We included primary reports that had at least one group of participants with cochlear implants, and had an experimental task that measured talker or voice perception. Each included study was also evaluated for quality of evidence.Results: The initial search resulted in 1239 references, which were first screened for inclusion and then evaluated in full. Thirty-nine studies examining talker identification, talker discrimimnation, and gender discrimination were included in the final review. The majority of studies were focused on adult postlingual cochlear implant users, with a few studies focused on prelingual implant users. As a group, CI users generally performed above chance in talker perception tasks, but performed worse than NH controls. Nonetheless, a subset of CI users reached the same level of performance as NH participants. CI users relied more heavily on fundamental frequency over vocal tract length cues to distinguish talkers compared to NH listeners. Within groups of CI users, there is moderate evidence for a bimodal benefit for talker perception, and there are mixed findings about the effects of hearing experience. Performance in talker discrimination tasks was related to other linguistic tasks, including word recognition. Conclusion: The current review highlights the challenges faced by CI users in tracking and recognizing voices and how they adapt to it. There is clear evidence that CI users can process indexical information, albeit differently and more effortfully than NH listeners. Recent work has begun to describe some of the factors that might ease the challenges of talker perception in CI users, but further high-quality research is needed to disentangle some of the mixed findings. We conclude by suggesting some future avenues of research to optimize real-world speech outcomes.


2020 ◽  
Vol 148 (4) ◽  
pp. 2618-2618
Author(s):  
William A. Yost ◽  
M. Torben Pastore ◽  
Philip Robinson

2020 ◽  
Vol 148 (4) ◽  
pp. 2763-2763
Author(s):  
Jayden J. Lee ◽  
Jessica A. Tin ◽  
Tyler K. Perrachione

2020 ◽  
Vol 63 (5) ◽  
pp. 1361-1375
Author(s):  
Jing Shao ◽  
Lan Wang ◽  
Caicai Zhang

Purpose The ability to recognize individuals from their vocalizations is an important trait of human beings. In the current study, we aimed to examine how congenital amusia, an inborn pitch-processing disorder, affects discrimination and identification of talkers' voices. Method Twenty Mandarin-speaking amusics and 20 controls were tested on talker discrimination and identification in four types of contexts that varied in the degree of language familiarity: Mandarin real words, Mandarin pseudowords, Arabic words, and reversed Mandarin speech. Results The language familiarity effect was more evident in the talker identification task than the discrimination task for both participant groups, and talker identification accuracy decreased as native phonological representations were removed from the stimuli. Importantly, amusics demonstrated degraded performance in both native speech conditions that contained phonological/linguistic information to facilitate talker identification and nonnative conditions where talker voice processing primarily relied on phonetics cues, including pitch. Moreover, the performance in talker processing can be predicted by the participants' musical ability and phonological memory capacity. Conclusions The results provided a first set of behavioral evidence that individuals with amusia are impaired in the ability of human voice identification. Meanwhile, it is found that amusia is not only a pitch disorder but is likely to affect the phonological processing of speech, in terms of using phonological information in native speech to analyze a talker's identity. The above findings expanded the understanding of the nature and scope of congenital amusia. Supplemental Material https://doi.org/10.23641/asha.12170379


2020 ◽  
Author(s):  
William A. Yost ◽  
M. Torben Pastore ◽  
Phillip Robinson

2019 ◽  
Vol 145 (6) ◽  
pp. EL469-EL475 ◽  
Author(s):  
Divya Ganugapati ◽  
Rachel M. Theodore

2019 ◽  
Vol 81 (4) ◽  
pp. 1088-1107 ◽  
Author(s):  
Deirdre E. McLaughlin ◽  
Yaminah D. Carter ◽  
Cecilia C. Cheng ◽  
Tyler K. Perrachione

Author(s):  
Tyler K. Perrachione

Listeners identify voices more accurately in their native language than an unknown, foreign language, in a phenomenon known as the language-familiarity effect in talker identification. This effect has been reliably observed for a wide range of different language pairings and using a variety of different methodologies, including voice line-ups, talker-identification training, and talker discrimination. What do listeners know about their native language that helps them recognize voices more accurately? Do listeners gain access to this knowledge when they learn a second language? Is linguistic competence necessary, or can mere exposure to a foreign language help listeners identify voices more accurately? This chapter reviews the more than three decades of research on the language-familiarity effect in talker identification, with an emphasis on how attention to this phenomenon can inform not only better psychological and neural models of memory for voices, but also better models of speech processing.


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