English Vowel Production by Native Mandarin and Hindi Speakers

Olagbaju, Yemi; Barkana, Buket D.; Gupta, Navarun

doi:10.1109/itng.2010.220

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…The issues mentioned above might be able to explain the discrepant findings learning should be given more attention in transfer studies. Most transfer studies attribute the discrepancies between Chinese English speakers' vowel productions and native speakers' vowel productions to the L1 influence without precisely considering and controlling the participants dialects background (e.g., Evanini & Huang, 2013;Olagbaju, Barkana, & Gupta, 2010;.…”

Section: Baseline English Native Providersmentioning

confidence: 99%

A Systematic Review: Exploring L2 Vowel Production from Revised Speech Learning Theory Perspective

Liu¹

2023

JSS

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Speech learning model aims to explain the variables contributing to the differences in L2 phonetic productions. Most previous studies comparing L2 vowel production with L1 vowel production mostly attribute the differences to the mother tongue inference, which is also proposed by Speech learning model. However, the past transfer studies show a number of discrepant findings even regarding the same L2 vowel production. Therefore, this systematic review collected past studies compared L2 vowel production with L1 vowel production to understand the causes to the discrepant findings. Relevant articles published 2000 onward were searched with key words, such as "L2 accented English", "vowel space", "L2 Formants", "Chinese-accented English", "comparing Chinese English" in the online database. In the initial search with the key words, 120 articles were found. After two screenings on titles and abstracts, and based on inclusion and exclusion criteria, 14 articles were kept to be reviewed. Another search was conducted by referring to the reference lists of the selected articles. Another 2 articles were added, which is 16 articles totally reviewed in this paper. This review starts with a review on the speech learning model. Then synthesizing and analyzing the collected articles are followed. Pedagogical implications and recommendations for future studies regarding the language transfers studies are discussed.

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Section: Baseline English Native Providersmentioning

confidence: 99%

A Systematic Review: Exploring L2 Vowel Production from Revised Speech Learning Theory Perspective

Liu¹

2023

JSS

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“…Several researchers have employed formants for the identification of dialects (Adank et al, 2007;Yan & Vaseghi, 2003). Olagbaju et al, (2010) in their study calculated the mean and standard deviation of the first three formants of vowels produced by Mandarin and Hindi speakers. Their findings highlighted that analysis of formant frequencies can contribute to a richer understanding of accent variation.…”

Section: F1 Vs F2 Formant Space Analysis For Vowels Of Hie and Biementioning

confidence: 99%

Identifying acoustic cues for dialect profiling: Policing in multilingual communities of India

Toppo

Sinha

2022

Indonesian J. Appl. Linguist.

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A multilingual country such as India with numerous languages and dialects provides fertile grounds for evasive language crimes. From threat letters to ransom demands, the scope of crime is huge. The cases of illegal immigrants have only added to the fragility of international boundaries especially, during political upheavals. This leads to further vulnerability of society and also creates challenges for the police and law enforcement agencies towards timely intervention. The purpose of the study is to exhibit dialectal variation in Indian English by comparing two varieties. The current paper is based on the acoustic analysis of Indian English spoken by two distinct groups with different mother tongues. Ten native speakers of Hindi and Bangla were recorded in an anechoic chamber. A phonetically balanced passage was selected to be read. The analysis is based on Native Language Influence Detection (Perkins Grant, 2018) to derive acoustic phonetic correlates that can be used as significant identifying markers to distinguish Indian English speakers of Bangla and Hindi speech communities. The paper highlights that dialect profiling in the Indian context can be efficiently correlated with formant frequencies and Voice Onset Time for speech data. Acoustic analysis was done on PRAAT. PRAAT was used in this study because it has often been used by other similar studies to measure desired acoustic parameters simultaneously. Formant frequencies were measured at the midpoint of the vowels in the PRAAT using the LPC formant measurement algorithm. The normalization procedure was applied to the measured formant frequencies of vowels. The research affirms that acoustic analysis can provide verifiable cues for NLID. The framework can be used in the detection of native language influence in speech-centric criminal cases. The acoustic analysis shows that Indian English has subvarieties that could help in dialect profiling. The variation in Indian English vowel patterns could be due to the influence of the native language of the speakers.

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“…While one might predict that MAE vowels common to both L1 and L2 may be most native-like, even for common vowels, MAE vowels appear to differ acoustically from AE vowels (Chen, 1999;Chen et al, 2001). Additionally, there is evidence that front vowels in MAE are acoustically more native-like than back vowels (Olagbaju, Barkana, & Gupta, 2010).…”

Section: Introductionmentioning

confidence: 99%

Vowel production in Mandarin accented English and American English: Kinematic and acoustic data from the Marquette University Mandarin accented English corpus

Berry

Johnson

2013

The Journal of the Acoustical Society of America

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Few electromagnetic articulography (EMA) datasets are publicly available, and none have focused systematically on non-native accented speech. We introduce a kinematic-acoustic database of speech from 40 (gender and dialect balanced) participants producing upper-Midwestern American English (AE) L1 or Mandarin Accented English (MAE) L2 (Beijing or Shanghai dialect base). The Marquette University EMA-MAE corpus will be released publicly to help advance research in areas such as pronunciation modeling, acoustic-articulatory inversion, L1-L2 comparisons, pronunciation error detection, and accent modification training. EMA data were collected at a 400 Hz sampling rate with synchronous audio using the NDI Wave System. Articulatory sensors were placed on the midsagittal lips, lower incisors, and tongue blade and dorsum, as well as on the lip corner and lateral tongue body. Sensors provide five degree-of-freedom measurements including threedimensional sensor position and two-dimensional orientation (pitch and roll). In the current work we analyze kinematic and acoustic variability between L1 and L2 vowels. We address the hypothesis that MAE is characterized by larger differences in the articulation of back vowels than front vowels and smaller vowel spaces compared to AE. The current results provide a seminal comparison of the kinematics and acoustics of vowel production between MAE and AE speakers.

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English Vowel Production by Native Mandarin and Hindi Speakers

Cited by 6 publications

References 8 publications

A Systematic Review: Exploring L2 Vowel Production from Revised Speech Learning Theory Perspective

A Systematic Review: Exploring L2 Vowel Production from Revised Speech Learning Theory Perspective

Identifying acoustic cues for dialect profiling: Policing in multilingual communities of India

Vowel production in Mandarin accented English and American English: Kinematic and acoustic data from the Marquette University Mandarin accented English corpus

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