Doctoral dissertation research: The representation, organization and access of lexical tone by native and nonnative Mandarin speakers

Ohio State University, The, Columbus OH

Investigators

Abstract

China and its over 1 billion Mandarin speakers play an increasingly important role in global affairs. Today more and more Americans of all ages are engaging with China by learning Mandarin as a foreign language. Yet, learning Mandarin poses many unique challenges; perhaps most daunting is the use of lexical tone, or pitch, to differentiate word meanings. Each syllable in Mandarin can be produced with up to four different pitch patterns--a sharp drop in a speaker's pitch could be the only difference between saying 'four' and 'to die.' Furthermore, tone can vary greatly according to a speaker's gender, age, speaking rate, as well as the position in the utterance and neighboring sounds. Given this complexity in the speech signal, how do native speakers of Mandarin effortlessly and rapidly process tone and how can non-native learners improve these processes? One solution involves probabilistic predictions about speech given the listener's knowledge of Mandarin's distributional properties. All languages exhibit regularly occurring patterns in speech: certain combinations of sounds are highly predictable based on prior experience with the language. Previous work by this research team has shown that native Mandarin speakers are highly sensitive to which tones pattern with which syllables and make use of this statistical learning during word recognition. Building on this research team's previous work, this project will examine how native and non-native Mandarin speakers store mental information about tones for newly learned words and how this information influences word recognition. This research will test 3 groups of speakers-- native Mandarin speakers, and native English speakers who either are learning Mandarin as a second language or have no previous experience with a tonal language. Participants will take part in a four-day artificial tonal language-learning paradigm. Specifically, the investigators will manipulate the co-occurrence of syllables and tones, as well as the number of speakers a participant hears, in order to monitor each group's sensitivity to the statistical distribution of the artificial language. Participants' word identification, pronunciation, and online eye-movement responses to speech stimuli will be measured across multiple sessions. This research program has implications not just for our cognitive understanding of how lexical tone is learned and used during word recognition, but also for our understanding of how to better teach and acquire a new tonal language like Mandarin Chinese.