Polyglot and Speech Corpus Tools: A System for Representing, Integrating, and Querying Speech Corpora

McAuliffe, Michael; Stengel-Eskin, Elias; Socolof, Michaela; Sonderegger, Morgan

doi:10.21437/interspeech.2017-1390

Cited by 7 publications

(6 citation statements)

References 15 publications

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“…The corpus contained 11863 qualifying word pairs, which were extracted along with existing time-aligned phonetic transcription using the Montreal Corpus Tools software (McAuliffe, Stengel-Eskin, Socolof, & Sonderegger, 2017). 4 The Pitt et al (2007) transcriptions were prepared automatically and subsequently hand-corrected by phonetically trained research assistants.…”

Section: Datasetmentioning

confidence: 99%

Predictability modulates pronunciation variants through speech planning effects: A case study on coronal stop realizations

Kilbourn-Ceron

Clayards

Wagner

2020

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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Predictability has been shown to be associated with many dimensions of variation in speech, including durational variation and variable omission of segments. However, the mechanism or mechanisms that underlie these effects are still unclear. This paper presents data on a new aspect of predictability in speech, namely how it affects allophonic variation. We examine two coronal stop allophones in English, flap and glottal stop, and find that their relationship with predictability is quite different from what is expected under current theories of probabilistic reduction in speech. Flapping is more likely when the word that follows is more predictable, but is not influenced by the frequency of the word itself, while glottal stops are more likely in words that are less predictable. We propose that the crucial distinction between these two allophones is how they are conditioned by phonological context. This, we argue, interacts with online speech planning processes and gives rise to variability for context-dependent allophones. This hypothesis offers a specific, testable mechanism for certain predictability effects, and has the potential to extend to other factors that contribute to variability in speech.

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Section: Datasetmentioning

confidence: 99%

Predictability modulates pronunciation variants through speech planning effects: A case study on coronal stop realizations

Kilbourn-Ceron

Clayards

Wagner

2020

Laboratory Phonology: Journal of the Association for Laboratory Phonology

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“…In order to standardize the acoustic analysis across corpora, the Integrated Speech Corpus Analysis (ISCAN) tool was developed for use in this kind of cross-dialectal study in the context of the SPADE project. This section provides a brief overview of the ISCAN system: see McAuliffe et al (2017bMcAuliffe et al ( , 2019 and the ISCAN documentation page for details of the implementation 4 . The process of deriving a dataset from raw corpus files consists of three major steps.…”

Section: Discussionmentioning

confidence: 99%

Toward “English” Phonetics: Variability in the Pre-consonantal Voicing Effect Across English Dialects and Speakers

Tanner

Sonderegger

Stuart‐Smith

et al. 2020

Front. Artif. Intell.

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Recent advances in access to spoken-language corpora and development of speech processing tools have made possible the performance of "large-scale" phonetic and sociolinguistic research. This study illustrates the usefulness of such a large-scale approach-using data from multiple corpora across a range of English dialects, collected, and analyzed with the SPADE project-to examine how the pre-consonantal Voicing Effect (longer vowels before voiced than voiceless obstruents, in e.g., bead vs. beat) is realized in spontaneous speech, and varies across dialects and individual speakers. Compared with previous reports of controlled laboratory speech, the Voicing Effect was found to be substantially smaller in spontaneous speech, but still influenced by the expected range of phonetic factors. Dialects of English differed substantially from each other in the size of the Voicing Effect, whilst individual speakers varied little relative to their particular dialect. This study demonstrates the value of large-scale phonetic research as a means of developing our understanding of the structure of speech variability, and illustrates how large-scale studies, such as those carried out within SPADE, can be applied to other questions in phonetic and sociolinguistic research.

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“…Using the transcripts from each corpus, we identified target instances of /b d g/ and /p t k/ using the PolyglotDB Python package (McAuliffe, Stengel-Eskin, Socolof, & Sonderegger, 2017), and compared the SpiCE bilinguals' productions to each of the monolingual comparison corpora. 4 The analyses described in the following studies report the results of mixed effects models for each study-cross-corpus comparisons, and a within-SpiCE analysis examining factors that influence language mode.…”

Section: General Methodsmentioning

confidence: 99%

Language contact within the speaker: Phonetic variation and crosslinguistic influence

Johnson¹,

Babel²

2021

Preprint

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A recent model of sound change posits that the direction of change is determined, at least in part, by the distribution of variation within speech communities (Harrington, Kleber, Reubold, Schiel, & Stevens, 2018; Harrington & Schiel, 2017). We explore this model in the context of bilingual speech, asking whether the less variable language constrains phonetic variation in the more variable language, using a corpus of spontaneous speech from early Cantonese-English bilinguals (Johnson, Babel, Fong, & Yiu, 2020). As predicted, given the phonetic distributions of stop obstruents in Cantonese compared to English, intervocalic English /b d g/ were produced with less voicing for Cantonese-English bilinguals and word-final English /t k/ were more likely to be unreleased compared to spontaneous speech from two monolingual English control corpora (Pitt, Johnson, Hume, Kiesling, & Raymond, 2005; Swan, 2016). Cantonese phonology is more gradient in terms of voicing initial obstruents (Clumeck, Barton, Macken, & Huntington, 1981; W. Y. P. Wong, 2006) than permitting releases of final obstruents, which is categorically prohibited Bauer & Benedict (2011); Khouw & Ciocca (2006). Neither Cantonese-English bilingual initial voicing nor word-final stop release patterns were significantly impacted by language mode. These results provide evidence that the phonetic variation in crosslinguistically linked categories in bilingual speech is shaped by the distribution of phonetic variation within each language, thus suggesting a mechanistic account for why some segments are more susceptible to cross-language influence than others in studies of mutual influence.

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Polyglot and Speech Corpus Tools: A System for Representing, Integrating, and Querying Speech Corpora

Cited by 7 publications

References 15 publications

Predictability modulates pronunciation variants through speech planning effects: A case study on coronal stop realizations

Predictability modulates pronunciation variants through speech planning effects: A case study on coronal stop realizations

Toward “English” Phonetics: Variability in the Pre-consonantal Voicing Effect Across English Dialects and Speakers

Language contact within the speaker: Phonetic variation and crosslinguistic influence

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