Detection of Non-native Speaker Status from Backwards and Vocoded Content-masked Speech
Abstract
This paper addresses the issue of speech rhythm as a cue to non-native pronunciation. In natural recordings, it is impossible to disentangle rhythm from segmental, subphonemic or suprasegmental features that may influence nativeness ratings. However, two methods of speech manipulation, that is, backwards content-masked speech and vocoded speech, allow the identification of native and non-native speech in which segmental properties are masked and become inaccessible to the listeners. In the current study, we use these two methods to compare the perception of content-masked native English speech and Polish-accented speech. Both native English and Polish-accented recordings were manipulated using backwards masked speech and 4-band white-noise vocoded speech. Fourteen listeners classified the stimuli as produced by native or Polish speakers of English. Polish and English differ in their temporal organization, so, if rhythm is a significant contributor to the status of non-native accentedness, we expected an above-chance rate of recognition of native and non-native English speech. Moreover, backwards content-masked speech was predicted to yield better results than vocoded speech, because it retains some of the indexical properties of speakers. The results
show that listeners are unable to detect non-native accent in Polish learners of English from backwards and vocoded speech samples.
Keywords
accent detection; non-native accent; content-masked speech; vocoded speech; backwards speech
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