Speaker-dependent Speech Recognition

Speaker-Dependent Speech Recognition is a speech recognition system that belongs to the class of automatic speech recognition methods and is distinguished by its reliance on prior acoustic models specifically trained for individual speakers, thereby optimizing performance for utterances from known speakers while typically requiring speaker-specific training data.

712

Publications

35.6K

Citations

1.6K

Authors

450

Institutions

Publications per year

2017–2026

122

Variants

Speaker-dependent Recognition

Authors

1.6K

  1. CL
    Chin‐Hui Lee

    Georgia Institute of Technology, United States

    16 publications · 657 citations

    15

    h-index

  2. RS
    Richard Schwartz

    National Institutes of Health, United States

    13 publications · 554 citations

    12

    h-index

  3. JL
    Jinyu Li

    Microsoft (United States), United States

    10 publications · 705 citations

    10

    h-index

  4. FK
    Francis Kubala

    Northeastern University, United States

    9 publications · 309 citations

    9

    h-index

  5. HL
    Haizhou Li

    National University of Singapore, Singapore

    9 publications · 471 citations

    9

    h-index

1–5 of 1.6K

Venues

  1. IEEE Transactions on Speech and Audio Processing

    27 publications · 1.9K citations

    22

    h-index

  2. International Conference on Acoustics, Speech, and Signal Processing

    Conference · 19 publications · 786 citations

    18

    h-index

  3. IEEE/ACM Transactions on Audio Speech and Language Processing

    TASLP · 18 publications · 943 citations

    16

    h-index

  4. Computer Speech & Language

    15 publications · 1.2K citations

    13

    h-index

  5. Speech Communication

    15 publications · 1.5K citations

    13

    h-index

1–5