2017 INTERSPEECH INTERSPEECH 2017

Lexical Adaptation to a Novel Accent in German: A Comparison Between German, Swedish, and Finnish Listeners

Abstract

Listeners usually adjust rapidly to unfamiliar regional and foreign accents in their native (L1) language. Non-native (L2) listeners, however, usually struggle when confronted with unfamiliar accents in their non-native language. The present study asks how native language background of L2 speakers influences lexical adjustments in a novel accent of German, in which several vowels were systematically lowered. We measured word judgments on a lexical decision task before and after exposure to a 15-min story in the novel dialect, and compared German, Swedish and Finnish listeners’ performance. Swedish is a Germanic language and shares with German a number of lexical roots and a relatively large vowel inventory. Finnish is a Finno-Ugric language and differs substantially from Germanic languages in both lexicon and phonology. The results were as predicted: descriptively, all groups showed a similar pattern of adaptation to the accented speech, but only German and Swedish participants showed a significant effect. Lexical and phonological relatedness between the native and non-native languages may thus positively influence lexical adaptation in an unfamiliar accent.

🌉 Interdisciplinary Bridge — Artificial Intelligence and Machine Learning
🧭 Keyword Pioneer — second language
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio