Segmental information drives adult bilingual phrase segmentation preference

ABSTRACT

In two artificial language learning experiments with four groups of highly proficient Basque-Spanish bilinguals and two groups of Spanish monolinguals, we examine the cues that allow adult listeners to parse new input into phrases. In addition, we investigate which factors lead bilinguals to switch between the segmentation strategies characteristic of their two languages. We show that segmental information drives bilinguals’ choice of a segmentation strategy when presented with an unfamiliar language. The language in which bilinguals are addressed during the study (i.e. the language of context) additionally modulates their segmentation preference, and this context language effect is found in L1Basque bilinguals but does not extend to L1Spanish bilinguals. The cause of this asymmetry is yet to be established. Finally, we show that adult monolinguals disregard statistical cues in favor of unfamiliar segmental information when in conflict. These results evidence that the available phrase segmentation cues are arranged hierarchically.

KEYWORDS:

• Bilingualism
• artificial language learning
• phrase segmentation
• segmental cues
• statistical cues
• context language effect

Acknowledgements

We wish to thank Adam Zawiszewski and Idoia Ros for their help running a subset of the participants.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Notes

1 We use the terms segmentation and parse interchangeably throughout the paper. In the present study, we examine adults’ abilities to extract phrases from new input, that is, to locate their boundaries. However, we do not wish to claim that the listeners process the semantic and syntactic information contained in these phrases.

2 With and without a concurrent visual facial correlate to auditory phrasal prosody, specifically head nodding (de la Cruz-Pavía et al. 2019).

3 Castañeda (1986) reports a mean VOT value for each of the six stops found in Spanish. Braunschweiler (1997) reports only two VOT values per type of stop in German: voiced vs. voiceless. One value refers to the release before long vowels, the other before short vowels. For comparability, we report here the mean VOT value of each type of stop — voiced vs. voiceless — averaging across contexts and stops that belong to the same type.

Additional information

Funding

This work was supported by Agence Nationale de la Recherche: [Grant Number SpeechCode—ANR-15-CE37-0009-01 and French Investissements d’Avenir Labex EFL Program—ANR-10-LABX-0083]; Eusko Jaurlaritza: [Grant Number BFI07.253, IT1169-19, IT1396-19]; H2020 European Research Council: [Grant Number Consolidator Grant 773202 ERC-2017-COG BabyRhythm]; Ministerio de Ciencia e Innovación: [Grant Number FFI2015-64183-P, FFI2016-80021-P].

Notes on contributors

Irene de la Cruz-Pavía

Irene de la Cruz-Pavía is a post-doctoral researcher at the CNRS and the Université de Paris (France). Her work investigates the cognitive mechanisms involved in the acquisition and processing of morphosyntax in mono- and bilingual populations.

Gorka Elordieta

Gorka Elordieta is an associate professor at the Department of Linguistics and Basque Studies of the University of the Basque Country (Spain). His main areas of research are prosody, intonation and the interface of phonology and morphosyntax.

Julián Villegas

Julián Villegas is an associate professor at the Computer Arts Laboratory of the University of Aizu (Japan). His work focuses on phonetics, psychoacoustics, and audio signal processing.

Judit Gervain

Judit Gervain is a Directrice de Recherche at the CNRS and the Université Paris Descartes (France). She specialises in developmental cognitive neuroscience.

Itziar Laka

Itziar Laka is a full professor at the Department of Linguistics and Basque Studies of the University of the Basque Country (Spain). Her work investigates language processing with a strong focus on syntax and bilingualism.