Thesis defense

Hearing Ethnicity: classification, stereotypization and processing of socially marked phonetic features in Modern Hebrew

Speaker(s)
Si Berrebi (LSCP)
Practical information
16 December 2021
2pm
LSCP

The thesis explores the relationship between social and phonological perception, relying on case studies from Modern Hebrew (MH). The social setting is the ethnically-based dichotomy between "Mizrahi" (Middle Eastern and North-African background) and "Ashkenazi" (European background) Jewish-Israelis.

Part I uses an ethnicity classification task to examine how phonetic variation affects ethnicity perception among native speakers. Speakers of various ethnic backgrounds recorded the same ~5 seconds long sentence used as stimuli. The results showed that some speakers whose speech did not include any of the markers known to be associated with ethnic identity were nonetheless found to sound "Mizrahi" or "Ashkenazi".

Part II investigates variation in the processing of the same variant, and in particular the ways in which the degree and context of experience with marked phonological variants affects online speech processing. It includes two series of experiments: the first targets the representations of speakers with different levels of exposure to the same variant; the second studies the role of perceived speaker's identity in the online processing of marked variants. Taken together, the results of part II contribute to our understanding of speech processing in the indexical (speaker-oriented) route the following insights: (i) Deep acquaintance with a vernacular can induce subtle predictions regarding production; even when a word was not illicit at the global (lexical) level, but only inconsistent with the identity of the speaker, speech recognition was affected. (ii) Presenting a persona who uses a marked variant can focus listeners' attention on a particular acoustic dimension, yielding significant differences in responses to the same stimuli.

Zoom likn : https://tau-ac-il.zoom.us/j/83624254892?pwd=RS8rcGtwVkxNWlFCMEthbFByVnR0QT09