Christopher Bergmann

The impact of language co-activation on L1 and L2 speech fluency

Fluent speech depends on the availability of well-established linguistic knowledge and routines for speech planning and articulation. A lack of speech fluency in late second-language (L2) learners may point to a deficiency of these representations, due to incomplete acquisition. Experiments on bilingual language processing have shown, however, that there are strong reasons to believe that multilingual speakers experience co-activation of the languages they speak. We have studied to what degree language co-activation affects fluency in the speech of bilinguals, comparing a monolingual German control group with two bilingual groups: 1) first-language (L1) attriters, who have fully acquired German before emigrating to an L2 English environment, and 2) immersed L2 learners of German (L1: English). We have analysed the temporal fluency and the incidence of disfluency markers (pauses, repetitions and self-corrections) in spontaneous film retellings. Our findings show that learners to speak more slowly than controls and attriters. Also, on each count, the speech of at least one of the bilingual groups contains more disfluency markers than the retellings of the control group. Generally speaking, both bilingual groups-learners and attriters-are equally (dis)fluent and significantly more disfluent than the monolingual speakers. Given that the L1 attriters are unaffected by incomplete acquisition, we interpret these findings as evidence for language competition during speech production.

L2 immersion causes non-native-like L1 pronunciation in German attriters

According to Flege׳s Speech Learning Model, the speech sounds of a bilingual׳s languages are contained in one common phonological space. This predicts bidirectional influence on the articulation of these speech sounds. We investigated the influence of a late-learned second language (L2) on the first language (L1) in a group of German L1 attriters in Anglophone North America (i.e., long-term emigrants in L2 immersion). These speakers were compared to a control group of monolingual German L1 speakers in two analyses: First, L1 speech samples of both groups were rated for native-likeness. Attriters sounded less native-like to raters, with 40% of the attriters rated below the monolingual range. Native-likeness was negatively associated with length of residence abroad and positively associated with L1 use. Second, formant analyses on four speech sounds of German—/aː/, /ɛ/, /ɔ/ and /l/—were conducted for attriters and controls. For these analyses, two attriter subgroups were formed: one with speakers who sounded native-like to raters and one with speakers who did not. It was hypothesised that the formants in both groups would shift in the direction of similar L2 speech sounds and that the shift would be stronger in non-native-like attriters. The first hypothesis was partly confirmed: At least one attriter group differed from the control group on one formant of /aː/ and /l/. These differences were consistent with predictions based on the L2. The second hypothesis was not confirmed: There was no evidence that the formants of the non-native-like attriters deviated more strongly from the monolingual baseline than those of the native-like attriters. Additionally, the formant values and the ratings were found to be only weakly associated, suggesting a different source of the perceptibly non-native-like pronunciation in some attriters.

Prolonged L2 immersion engenders little change in morphosyntactic processing of bilingual natives

Bilingual and monolingual language processing differ, presumably because of constant parallel activation of both languages in bilinguals. We attempt to isolate the effects of parallel activation in a group of German first-language (L1) attriters, who have grown up as monolingual natives before emigrating to an L2 environment. We hypothesized that prolonged immersion will lead to changes in the processing of morphosyntactic violations. Two types of constructions were presented as stimuli in an event-related potential experiment: (1) verb form combinations (auxiliaries+past participles and modals+infinitives) and (2) determiner–noun combinations marked for grammatical gender. L1 attriters showed the same response to violations of gender agreement as monolingual controls (i.e. a significant P600 effect strongest over posterior electrodes). Incorrect verb form combinations also elicited a significant posterior P600 effect in both groups. In attriters, however, there was an additional posterior N400 effect for this type of violation. Such biphasic patterns have been found before in L1 and L2 speakers of English and might reflect the influence of this language. Generally, we interpret our results as evidence for the stability of the deeply entrenched L1 system, even in the face of L2 interference.

Designing research on bilingual development: Behavioral and neurolinguistic experiments

Chapter 1. Introduction by Monika S. Schmid.- Chapter 2. Multi-factorial studies: Populations and linguistic features by Monika S. Schmid.- Chapter 3. The multi-lab, multi-language, multi-method challenge By Bregtje J. Seton and Laurie A. Stowe.- Chapter 4. Collecting and analyzing spontaneous speech data by Christopher Bergmann.- Chapter 5. Eye-tracking and the visual world paradigm by Sanne Meike Berends, Susanne M. Brouwer and Simone A. Sprenger.- Chapter 6. EEG and event-related brain potentials by Nienke Meulman, Bregtje J. Seton and Laurie A. Stowe.

Collecting and Analyzing Spontaneous Speech Data

Spontaneous speech samples can serve several purposes within a language acquisition study. First, spontaneous speech can be used in various ways to assess the proficiency of individuals, for example via accent ratings, measures of lexical variability, and frequency of different types of errors. It can also be an object of analysis in its own right, for example in examining interactions between linguistic variables and potential trade-off effects, including factors such as the use of fixed expressions, sentence complexity or speech rate as well as the interaction between them. Finally, it can provide a comparison of production with processing or comprehension measures. While the analysis of this sort of data is not, in principle, different for a large scale study like this than for a single dedicated study, the versatility of information it allows the researcher to assess is easy to underestimate. This chapter will discuss the collection, transcription, coding and analysis of spontaneous speech samples, serving as an exploration and reminder of some of those possibilities as well as an introduction to how to make use of them.