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        <title>An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction</title>
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    <name type="personal">
        <namePart type="given">Xinyuan</namePart>
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        <namePart type="given">Charbel</namePart>
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    <name type="personal">
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        <namePart type="family">Kuo</namePart>
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    <name type="personal">
        <namePart type="given">Priscilla</namePart>
        <namePart type="given">Kan</namePart>
        <namePart type="family">John</namePart>
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    <name type="personal">
        <namePart type="given">Hanna</namePart>
        <namePart type="family">Suominen</namePart>
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            <namePart type="given">Daniel</namePart>
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    <abstract>Speech visualisations are known to help language learners to acquire correct pronunciation and promote a better study experience. We present a two-step approach based on two established techniques to display tongue tip movements of an acoustic speech signal on a vowel space plot. First we use Energy Entropy Ratio to extract vowels; and then we apply Linear Predictive Coding root method to estimate Formant 1 and Formant 2. We invited and collected acoustic data from one Modern Standard Arabic (MSA) lecture and four MSA students. Our proof of concept was able to reflect differences between the tongue tip movements in a native MSA speaker to those of a MSA language learner. This paper addresses principle methods for generating features that reflect bio-physiological features of speech and thus, facilitates an approach that can be generally adapted to languages other than MSA.</abstract>
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        <date>2020-12</date>
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%0 Conference Proceedings
%T An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction
%A Chao, Xinyuan
%A El-Khaissi, Charbel
%A Kuo, Nicholas
%A John, Priscilla Kan
%A Suominen, Hanna
%Y Kim, Maria
%Y Beck, Daniel
%Y Mistica, Meladel
%S Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association
%D 2020
%8 December
%I Australasian Language Technology Association
%C Virtual Workshop
%F chao-etal-2020-automatic
%X Speech visualisations are known to help language learners to acquire correct pronunciation and promote a better study experience. We present a two-step approach based on two established techniques to display tongue tip movements of an acoustic speech signal on a vowel space plot. First we use Energy Entropy Ratio to extract vowels; and then we apply Linear Predictive Coding root method to estimate Formant 1 and Formant 2. We invited and collected acoustic data from one Modern Standard Arabic (MSA) lecture and four MSA students. Our proof of concept was able to reflect differences between the tongue tip movements in a native MSA speaker to those of a MSA language learner. This paper addresses principle methods for generating features that reflect bio-physiological features of speech and thus, facilitates an approach that can be generally adapted to languages other than MSA.
%U https://aclanthology.org/2020.alta-1.6
%P 54-64

Markdown (Informal)

[An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction](https://aclanthology.org/2020.alta-1.6) (Chao et al., ALTA 2020)

• An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction (Chao et al., ALTA 2020)

ACL

• Xinyuan Chao, Charbel El-Khaissi, Nicholas Kuo, Priscilla Kan John, and Hanna Suominen. 2020. An Automatic Vowel Space Generator for Language Learner Pronunciation Acquisition and Correction. In Proceedings of the 18th Annual Workshop of the Australasian Language Technology Association, pages 54–64, Virtual Workshop. Australasian Language Technology Association.