Proceedings of the Annual Meeting of the Cognitive Science Society

Adult speech perception is tuned to efficiently process native phonetic categories, causing difficulties with certainnon-native categories. For example, Japanese has no equivalent of the distinction between American English /r/ and /l/ and na-tive speakers of Japanese have a hard time discriminating between these two sounds. Here, we ask whether standard AutomaticSpeech Recognition (ASR) systems trained on large corpora of continuous speech can make correct quantitative predictionsregarding such non-native phonetic category perception effects. By training an ASR system on language L1 and evaluatingit on language L2, we obtain predictions for a native L1 speaker tested on L2 phonetic contrasts. Using a variety of L1 andL2, we show that ASR models correctly predict several well-documented effects. Beyond the immediate results, our evaluationmethodology, based on a machine version of ABX discrimination tasks, opens the possibility of a more systematic investigationof computational models of phonetic category perception.