The Speech Accent Archive: towards a typology of English accents

Weinberger, Steven H.; Kunath, Stephen

doi:10.1163/9789401206884_014

Cited by 29 publications

(19 citation statements)

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“…The second dataset was The Speech Accent Archive [27], speech corpus comprised of English speakers from different countries and regions. All speakers read the same prompt -a simple message about picking up grocery items from the store.…”

Section: Methodsmentioning

confidence: 99%

Assessing the efficacy of benchmarks for automatic speech accent recognition

Bock¹,

Shamir²

2015

Proceedings of the 8th International Conference on Mobile Multimedia Communications

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Speech accents can possess valuable information about the speaker that can be used in intelligent multimedia-based human-computer interfaces. The performance of algorithms for automatic classification of accents is often evaluated using audio datasets that include recording samples of different people, representing different accents. Here we describe a method that can detect bias in accent datasets, and apply the method to two accent identification datasets to reveal the existence of dataset bias, meaning that the datasets can be classified with accuracy higher than random even if the tested algorithm has no ability to analyze speech accent. We used the datasets by separating one second of silence from the beginning of each audio sample, such that the one-second sample did not contain voice, and therefore no information about the accent. An audio classification method was then applied to the datasets of silent audio samples, and provided classification accuracy significantly higher than random. These results indicate that the performance of accent classification algorithms measured using some accent classification benchmarks can be biased, and can be driven by differences in the background noise rather than the auditory features of the accents.

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Section: Methodsmentioning

confidence: 99%

Assessing the efficacy of benchmarks for automatic speech accent recognition

Bock¹,

Shamir²

2015

Proceedings of the 8th International Conference on Mobile Multimedia Communications

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“…(Translation: "It was spring and the sun was shining, elms were in bloom, water came from fountains, rooks flew around and goldfish as big as dolphins were shooting through the glistening water.") The L2 speech samples consisted of the first two sentences of the elicitation paragraph used in the Speech Accent Archive (Weinberger & Kunath, 2011): Please call Stella. Ask her to bring these things from the store: six spoons of fresh snow peas, five thick slabs of blue cheese, and maybe a snack for her brother Bob.…”

Section: Methodsmentioning

confidence: 99%

The Impact of Alcohol on L1 versus L2

et al. 2020

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Alcohol intoxication is known to affect many aspects of human behavior and cognition; one of such affected systems is articulation during speech production. Although much research has revealed that alcohol negatively impacts pronunciation in a first language (L1), there is only initial evidence suggesting a potential beneficial effect of inebriation on articulation in a non-native language (L2). The aim of this study was thus to compare the effect of alcohol consumption on pronunciation in an L1 and an L2. Participants who had ingested different amounts of alcohol provided speech samples in their L1 (Dutch) and L2 (English), and native speakers of each language subsequently rated the pronunciation of these samples on their intelligibility (for the L1) and accent nativelikeness (for the L2). These data were analyzed with generalized additive mixed modeling. Participants’ blood alcohol concentration indeed negatively affected pronunciation in L1, but it produced no significant effect on the L2 accent ratings. The expected negative impact of alcohol on L1 articulation can be explained by reduction in fine motor control. We present two hypotheses to account for the absence of any effects of intoxication on L2 pronunciation: (1) there may be a reduction in L1 interference on L2 speech due to decreased motor control or (2) alcohol may produce a differential effect on each of the two linguistic subsystems.

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“…The Speech Accent archive [26] is digitally available at http://accent.gmu.edu and contains a large sample of speech samples in English from people with various language backgrounds. Each speaker read the same paragraph of 69 words (55 of which are unique) in English:…”

Section: Methodsmentioning

confidence: 99%

“…All speech samples were transcribed by three phonetically trained transcribers (consensus was reached in the few cases where the transcriptions differed; [26]) according to the International Phonetic Alphabet (IPA). The transcriptions include diacritics, and the associated audio files are available.…”

Section: Methodsmentioning

confidence: 99%

A Cognitively Grounded Measure of Pronunciation Distance

et al. 2014

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In this study we develop pronunciation distances based on naive discriminative learning (NDL). Measures of pronunciation distance are used in several subfields of linguistics, including psycholinguistics, dialectology and typology. In contrast to the commonly used Levenshtein algorithm, NDL is grounded in cognitive theory of competitive reinforcement learning and is able to generate asymmetrical pronunciation distances. In a first study, we validated the NDL-based pronunciation distances by comparing them to a large set of native-likeness ratings given by native American English speakers when presented with accented English speech. In a second study, the NDL-based pronunciation distances were validated on the basis of perceptual dialect distances of Norwegian speakers. Results indicated that the NDL-based pronunciation distances matched perceptual distances reasonably well with correlations ranging between 0.7 and 0.8. While the correlations were comparable to those obtained using the Levenshtein distance, the NDL-based approach is more flexible as it is also able to incorporate acoustic information other than sound segments.

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The Speech Accent Archive: towards a typology of English accents

Cited by 29 publications

References 0 publications

Assessing the efficacy of benchmarks for automatic speech accent recognition

Assessing the efficacy of benchmarks for automatic speech accent recognition

The Impact of Alcohol on L1 versus L2

A Cognitively Grounded Measure of Pronunciation Distance

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