A matched-guise technique was used, which meant that one male speaker produced all three tested accents. This technique has the advantage of controlling for the influence of paralinguistic features like voice quality. We discussed different voice evaluation paradigms in Nejjari et al. (2019) leading us to conclude that the matched-guise technique constitutes the most optimal speech evaluation paradigm. The male matched-guise speaker in our study had been assessed in a prior accentedness experiment, which showed that only he could authentically produce the three accents: (1) BrE, (2) AmE, and (3) DE, the typical English accent of L1 speakers of Dutch (see Nejjari et al., 2019 for detailed discussion on the matched-guise technique itself, the reason for employing the matched-guise technique, and the matched-guise speaker selection process). In the current study, “standard” accents of British and American English refer to the accents generally associated with the national accent norm of the nations in which they originate. Both Englishes are used as models in L2 English education around the world (Robinson, 2019). A typical Dutch English accent contains features that L1 speakers of Dutch and others familiar with Dutch and Dutch English will recognize as such. For example, because Dutch lacks dental consonants [ð] as in this, mother, breathe and [θ] as in think, Martha, breath, they are often mispronounced as stop consonants, [d] and [t] respectively, by Dutch speakers of English. Dutch also lacks voiced fricatives and plosives in the coda, causing the voiced obstruents of English to generally be pronounced as voiceless in Dutch speakers’ English (e.g. live, badge, bad, bag will be pronounced with [f, tʃ, t, k]) (Gussenhoven & Broeders, 1997). As no standard has been defined for Dutch English, this accent is referred to as ‘typical’ in the present study (cf. Nejjari et al., 2019).

Listeners only heard one of the nine matched-guise speech samples, preventing listeners from deducing that we used a matched-guise technique. We included (speech samples from) six male control speakers as stimuli: two L1 speakers of BrE, two L1 speakers of AmE, two DE speakers. All but one had been assessed on the representativeness of their accents in the same accentedness experiment as the matched-guise speaker (see Nejjari et al., 2019). The speaker who was not assessed was one of the DE control speakers. He was generally regarded by experienced linguists and Dutch language specialists as a representative speaker of DE. One further male speaker produced a speech sample that was presented to all listeners at the beginning of the experiment (the filler speech sample) to familiarize them with the task. The filler speaker had also been selected from the prior study as an L1 and standard speaker of British English (Nejjari et al., 2019).

To ensure that the nine (plus one filler) matched-guise samples could be evaluated in each context for each accent, to avoid repeating the content of each context, and to limit any order effect, 18 listener groups were created, aiming to collect approximately 30 listeners per group (Table 1).

Listeners were highly educated (highest degree attained: 12.3 % A-level; 51.2 % bachelor; 27.6 % master; 2.3 % PhD; 6.3 % other) native speakers of Dutch (mean age 39; 60 % female, 40 % male) with no background in linguistics. They were selected because they represent the part of Dutch society most likely to use English in educational and professional settings (Bouma, 2016; Lizzini et al., 2017). To understand whether self-reported English fluency impacted speech understandability, the listeners were asked to estimate their English language skills (listening, reading, speaking, writing) on a 5-point Likert scale (1: very low; 2: low; 3: average; 4: high; 5: like a native speaker). Ninety-two percent indicated that their skills in all four areas were average or higher.

Participants were asked to indicate what they believed the speakers’ country of origin was. Over 92 % correctly indicated that the DE matched-guise speech sample was by a speaker from the Netherlands. For the BrE speech sample 88 % correctly indicated that the speech sample was produced by a speaker from Great Britain, and over 81 % correctly indicated that the AmE matched-guise speech sample was by a speaker from the United States. Responses of listeners who were not able to correctly identify speakers’ country of origin were excluded, as these could reflect interfering associations with other speaker groups, and thus with other accents than those under study.

In order to answer the first two RQ s, the responses by listeners who had correctly identified the speaker’s country of origin were included in the analyses (N = 392). To answer RQ3, however, correlations were calculated using all responses (N = 545), so as to provide a better assessment of the relationship between the speech understandability dimensions and English language skills, based on the larger range of English skills in the full sample.

Three texts, (1) an introduction to a marketing lecture, (2) an art gallery audio tour segment and (3) a job pitch for a retail management position, were used as the basis for the speech samples. One filler text on a general topic was used to start each questionnaire and allow listeners to get accustomed to the questions (links and texts: see appendix).

All but the filler text reflect three contexts (independent variable context) in which English is an important lingua franca: higher education, tourism, and international business (Gerritsen et al., 2016). Every listener evaluated all three contexts in the same order. To ensure realistic topics and content, the lecture, audio tour, and filler texts were selected from an IELTS Academic English listening test and the job pitch text from a human resources webpage. The matched-guise speaker produced the three accents in all three contexts, resulting in nine speech samples. The six control speakers produced English in their L1 accents (DE, BrE, AmE) in the three contexts, resulting in 18 speech samples, and the additional speaker produced one filler speech sample on a general topic in BrE.

An online survey was conducted via a student Facebook page and the online data collection service Qualtrics. This approach enabled the participation of many listeners, but the disadvantage was that many listeners did not complete the questionnaire or produced repetitive or nonsense response patterns. Approximately 41 % of the original data was discarded, resulting in data from 545 listeners. Reasons for excluding data included: incomplete questionnaires (approximately 25 %); nonsense answers or symbols and /or only neutral answers (approximately 15 % of the original data). Listeners who did not speak the required L1 were also excluded (1 %). The median questionnaire duration was a little over 16 minutes for all listeners, including the excluded responses.

Descriptives and frequencies were calculated to establish means and percentages of listener characteristics and responses. We used ANOVA s when the dependent variable was continuous and logistic regression when it was binomial (two values only). The factor analyses we applied to trace underlying dimensions in speaker evaluations were principal component analyses, with varimax rotation.

In general, speech understandability was high: comprehensibility was 89.2 %, interpretability was 82.2 %. The mean number of correctly transcribed words (intelligibility) was 9.23 (81.0 %), which is fairly high given the maximum correct score of 11 (Lecture, Job Pitch) or 12 (Audio Tour) words.

Results for intelligibility (proportion correct words) in relation to context and accent are shown in Figure 1, with 95 % confidence intervals. They show substantial overlap in the confidence intervals between bars, indicating that there are no strong differences between the accents and the contexts. An analysis of variance was applied to investigate the effects of context and accent and their interaction. There was an interaction effect (F(4,383) = 2.84, p = .02, η_p² = .03). There was a main effect for accent (F(2,383) = 4.30, p = .01, η_p² = .02), but not for context (F(2,383) = 1.27, p = .28, η_p² = .01). However, the post-hoc test (HSD) for accent did not show significant differences.

Results for comprehensibility in relation to context and accent are shown in Figure 2, with 95 % confidence intervals. There are no error bars for the Lecture in British and American English because the comprehension scores were 100 %. The remaining error bars show substantial overlap in the confidence intervals between bars, indicating that there are no strong differences between the three accents and the three contexts. A logistic regression (comprehensibility is a yes/no variable) was applied to test the effects of context and accent as well as their interaction. The interaction effect could be removed (Deviance score = 5.58, df = 4, p = .23). The same applied to accent in the next step (Deviance score = 1.80, df = 2, p = .41), but not for the remaining factor, context (Wald = 17.77, df = 2, p < .01). Post-hoc analysis (Bonferroni) revealed that the Lecture was comprehended better than the Audio Tour and Job Pitch.

Results for interpretability in relation to context and accent are shown in Figure 3, with 95 % confidence intervals. They demonstrate substantial overlap in the confidence intervals between bars, indicating that there are no strong differences between the three accents and three contexts. A logistic regression (interpretability is a yes/no variable) was applied to test the effects of context and accent as well as their interaction. The interaction effect could be removed (Deviance score between the model with the interaction and the model without interaction was 3.00, df = 4, p = .56). The same applied to accent in the next step (Deviance score = .42, df = 2, p > .05), but not for the remaining factor, context (Wald = 33.85, df = 2, p < .01). Post-hoc analysis (Bonferroni) revealed that interpretability was higher for the Lecture than the Audio Tour and Job Pitch.

Interpretability showed a positive, but weak, correlation with comprehensibility (r(545) = .26, p < .01) and intelligibility (r(545) = .20, p < .01). Comprehensibility showed a weak, positive correlation with intelligibility (r(545) = .13, p < .01). To check whether their self-reported language skills had an effect on speech understandability, correlations were computed with the three understandability variables. None were significant: interpretability: r(544) = .07, p = .11; comprehensibility: r(544) = –.02, p = .70; intelligibility: r(545) = .15, p = .06.

Results for status in relation to context and accent are shown in Figure 4, with 95 % confidence intervals. An analysis of variance was applied to investigate the effects of context and accent and their interaction. There was no interaction effect (F(4,383) = .53, p = .72, η_p² = .01). There was a main effect for accent (F(2,383) = 106.86, p < .01, η_p² = .36), but not for context (F(2,383) = 2.15, p = .12, η_p² = .01). Post-hoc comparisons (HSD) showed higher status for British English (M = 3.87, SD = .59) and American English (M = 3.69, SD = .57) compared to Dutch English (M = 2.77, SD = .73, p < .001).

Results for affect in relation to context and accent are shown in Figure 5, with 95 % confidence intervals. An analysis of variance was applied to investigate the effects of context and accent and their interaction. There was no interaction effect (F(4, 381) = 1.90, p = 11, η_p² = .02). There was no main effect for accent (F(2, 381) = 1.07, p = .31, η_p² = .01), but there was for context (F(2, 381) = 20.29, p < .01, η_p² = .10). Post-hoc comparisons (HSD) showed that the Audio Tour (M = 3.27, SD = .67) and Lecture (M = 3.22, SD = .74) aroused higher affect than the Job Pitch (M = 2.73, SD = .77, p < .001).

The results for dynamism are shown in Figure 6, with 95 % confidence intervals. An analysis of variance was applied to investigate the effects of context and accent and their interaction. There was an interaction effect (F(4,384) = 75.59, p < .01, η_p² = .06). There was no main effect for accent (F(2,384) = 1.42, p = .24, η_p² = .01), but there was for context (F(2,384) = 8.19, p < .01, η_p² = .04). Post-hoc comparisons (HSD) showed that Job Pitch (M = 2.97, SD = .78) evoked lower dynamism than the Audio Tour (M = 3.42, SD = .72) and Lecture (M = 3.26, SD = .71, p < .01), but the interaction clarified that this was due to the negative evaluation of the Dutch English Job Pitch.

Table 4 gives the correlations between speech understandability and speaker evaluations. There was only one negative correlation between comprehensibility and affect, but with a low value (r = -.11, p = .03).

The effects of accent and context on speech understandability (RQ1) are only significant for context. Accent did not influence speech understandability. This indicates that Dutch-accented English is as comprehensible as standard British and American English.

Context had an effect on interpretability and comprehensibility. The Lecture was more interpretable and comprehensible than the Audio Tour and the Job Pitch regardless of accent. Most listeners were highly educated, and might have had more frequent experience with academic educational settings. This concurs with Cargile (1997), who found that if listeners were confronted with an accent in a unexpected context, their responses to that speaker were negatively affected.

Speech understandability was high for all accents and contexts. The experiment was conducted with highly educated Dutch listeners who are generally regarded as having good English language skills (EF, 2018). This could mean that our listeners had high enough English fluency to easily deal with the content in our stimuli.

The high speech understandability caused a ceiling effect, which could have obscured the observed interpretability effects, and also contributed to weak, positive correlations between the three dimensions. This means that, when listeners could decipher words and phrases (intelligibility), this positively influenced their ability to understand them (comprehensibility) and to interpret speaker’s intention (interpretability). Comprehensibility and interpretability were measured by asking listeners to confirm or deny the validity of a statement on the content (comprehensibility) and communicative purpose (interpretability) of each sample. This method might have positively biased results; however, the positive correlation between the three components suggests that higher intelligibility helps comprehensibility and interpretability.

With regard to the effects of accent and context on speaker evaluations (RQ2), it can be concluded that having a Dutch English accent has a negative effect on a speaker’s status compared with standard British and American English. Context has no effect on the perceived status of a speaker. This indicates that accent matters more than context in perceptions of speaker status.

In terms of perceptions of affect and dynamism, context appears to be more important than accent, because context had an effect on affect and dynamism, with the Job Pitch context evoking lower affect and dynamism compared to the Lecture and Audio Tour contexts. Yet, even though the means for all three contexts were mostly neutral, and despite the fact that for dynamism and context the statistically significant results were caused by the Dutch English job pitch, it is striking that the Job Pitch context evoked such a negative response.

The above results concur with previous research that found that L1 and L2 speakers of English tend to assign L2 English accents lower status compared to L1 English accents, including their own L2 accent in English (e.g. Nejjari et al., 2012; Cargile, 1997; Dalton-Puffer et al., 1997; He & Zhang, 2010; Hendriks et al., 2016; Lindemann, 2003; Matsuura et al., 1994; McKenzie, 2008; Ryan & Bulik, 1982). In line with other research, our results showed that an L2 accent does not necessarily evoke lower affect (Nejjari et al., 2012; Hendriks et al., 2016) or dynamism (Nejjari et al., 2020), and that speaker evaluations can be impacted by context (Cargile, 1997).

The last research question focused on correlations between speech understandability and speaker evaluations (RQ3). Status and dynamism were not correlated with speech understandability. This means that a listener’s evaluation of the status and dynamism of a speaker is not related to their ability to comprehend a speaker. For affect there was a weak, negative correlation with comprehensibility. These results contradict Nejjari et al. (2012), who found a positive correlation between status and intelligibility and comprehensibility as well as between affect and comprehensibility. The explanation may be that their 2012 study involved British listeners, half of whom were not familiar with Dutch accented-English, who reacted to standard British English accent and two degrees of Dutch-accented English. These listeners probably needed to put more effort into comprehending accents and content than the L1 speakers of Dutch in the current study, who were all familiar with all three accents. They achieved high levels of speech understandability, resulting in the ceiling effect discussed above.

This study has a number of limitations. First, we only had one, male matched-guise speaker, because it was extremely challenging to find a speaker who could produce representative native as well as non-native English accents. However, future matched-guise studies could benefit from more diverse matched guise speakers. Second, the contexts for the questionnaire versions were presented in one order (filler, Lecture, Audio Tour, Job Pitch) without counterbalancing. We did not apply counterbalancing as this would have resulted in more questionnaire versions which would have required more respondents. We recommend counterbalancing for future studies. Third, the listeners were assumed to represent people who would likely be familiar with the three selected contexts. With hindsight, selecting professionals who regularly interact in these contexts, such as HR managers in the job interview context, would have been better.

The results for context provide nuance to earlier L1 and L2 accentedness studies. Future research should investigate other contexts and L2 and L1 accents to help language learners understand the effects of their accents and provide insights into which accents are deemed desirable for which contexts. The assessment of speech understandability in terms of Kachru and Smith’s (2008) three components yielded results that provide useful insights into the levels at which listeners are able to understand speech. However, the specific method employed to measure comprehensibility and interpretability resulted in high scores, ceiling effects, and weak correlations between the speech understandability dimensions. This suggests that the questions might have positively impacted the results. Therefore, this method should be further validated with listener groups with various English language levels and language backgrounds. While the use of the matched-guise technique contributed to the validity of our results, since they cannot be attributed to voice characteristics of individual speakers (as might have been the case with verbal guises), future studies should aim to use more than one matched-guise speaker.

Although our methodology yielded insightful results in terms of the understanding and evaluations of speakers, future research should assess how L2 and L1 English accents affect L1 and L2 English speakers’ behavior in specific contexts (see e.g. Purnell et al., 1999). With the increased globalization of academia and the job market, it is relevant to investigate how people view one another and behave towards each other on the basis of accents in these particular communication contexts.

Accent training aimed at becoming as L1 as possible for advanced Dutch learners of English need not be emphasized in language teaching when the aim is to be understandable and to evoke higher affect and dynamism. However, accent training to sound like an L1 speaker can be beneficial if the aim of language teaching is to evoke perceptions of high status. As context was shown to affect attitudes towards speakers, creating awareness of such potential effects can help learners understand the impression they make in English in different contexts.