Automatic Pronunciation Scoring

Automatic Pronunciation Scoring is a computational assessment method that systematically evaluates the accuracy and fluency of non-native speech production by comparing acoustic features of spoken input to native-like pronunciation norms.

99

Publications

4.4K

Citations

274

Authors

95

Institutions

Publications per year

2017–2026

29

Variants

Automated Pronunciation Scoring

Authors

274

  1. HF
    Horacio Franco

    SRI International, United States

    9 publications · 1K citations

    9

    h-index

  2. LN
    Leonardo Neumeyer

    SRI International, United States

    7 publications · 870 citations

    7

    h-index

  3. KZ
    Klaus Zechner

    Educational Testing Service, United States

    6 publications · 412 citations

    6

    h-index

  4. HS
    Helmer Strik

    Radboud University Nijmegen, Netherlands

    6 publications · 299 citations

    6

    h-index

  5. CC
    Catia Cucchiarini

    Radboud University Nijmegen, Netherlands

    5 publications · 283 citations

    5

    h-index

1–5 of 274

Venues

  1. Speech Communication

    8 publications · 1.3K citations

    8

    h-index

  2. Computer Speech & Language

    4 publications · 214 citations

    4

    h-index

  3. ETS Research Report Series

    3 publications · 109 citations

    3

    h-index

  4. ReCALL

    2 publications · 51 citations

    2

    h-index

  5. ACM Transactions on Accessible Computing

    TACCESS · 2 publications · 53 citations

    2

    h-index

1–5