Likelihood Ratio Framework

Likelihood Ratio Framework is a statistical inference methodology in forensic science and speaker identification that quantifies the strength of evidence by computing the ratio of the probability of observing the evidence under the hypothesis that the speech samples originate from the same speaker to the probability under the hypothesis that they originate from different speakers.

779

Publications

50.9K

Citations

4.4K

Authors

1K

Institutions

Publications per year

2017–2026

147

Authors

4.4K

  1. GS
    Geoffrey Stewart Morrison

    UNSW Sydney, Australia

    12 publications · 594 citations

    12

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  2. GZ
    Grzegorz Zadora

    Centralne Laboratorium Kryminalistyczne Policji, Poland

    14 publications · 429 citations

    11

    h-index

  3. JG
    Joaquín González-Rodríguez

    Universidad Autónoma de Madrid, Spain

    11 publications · 559 citations

    11

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  4. JB
    John Buckleton

    New Zealand Institute for Public Health and Forensic Science, New Zealand

    9 publications · 274 citations

    10

    h-index

  5. DJ
    D. J. B. Smith

    University of Hertfordshire, United Kingdom

    9 publications · 2.1K citations

    9

    h-index

1–5 of 4.4K

Venues

  1. The Annals of Statistics

    16 publications · 1K citations

    15

    h-index

  2. IEEE Transactions on Information Theory

    18 publications · 1.5K citations

    15

    h-index

  3. Journal of Forensic Sciences

    JOFS · 16 publications · 640 citations

    14

    h-index

  4. IEEE Transactions on Signal Processing

    15 publications · 2.2K citations

    14

    h-index

  5. Forensic Science International

    14 publications · 488 citations

    13

    h-index

1–5