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Vowel Inherent Spectral Change

1. Aufl., 2012

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An empirical estimate of the precision of likelihood ratios from a forensic-voice-comparison system

Forensic science international, 2011-05, Vol.208 (1), p.59-65

2011

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The impact in forensic voice comparison of lack of calibration and of mismatched conditions between the known-speaker recording and the relevant-population sample recordings

Forensic science international, 2018-02, Vol.283, p.e1-e7

Morrison, Geoffrey Stewart

2018

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Tutorial on logistic-regression calibration and fusion:converting a score to a likelihood ratio

Australian journal of forensic sciences, 2013-06, Vol.45 (2), p.173-197

Morrison, Geoffrey Stewart

2013

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Admissibility of Forensic Voice Comparison Testimony in England and Wales

Criminal law review, 2018-01 (1), p.20

Morrison, Geoffrey Stewart

2018

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Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science

Forensic science international. Synergy, 2022-01, Vol.5, p.100270-100270, Article 100270

Morrison, Geoffrey Stewart

2022

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In the context of forensic casework, are there meaningful metrics of the degree of calibration?

Forensic science international. Synergy, 2021-01, Vol.3, p.100157-100157, Article 100157

Morrison, Geoffrey Stewart

2021

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Empirical test of the performance of an acoustic-phonetic approach to forensic voice comparison under conditions similar to those of a real case

Forensic science international, 2017-08, Vol.277, p.30-40

2017

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Speaker identification in courtroom contexts – Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology

Forensic science international, 2022-12, Vol.341, p.111499-111499, Article 111499

2022

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Speaker identification in courtroom contexts – Part II: Investigation of bias in individual listeners’ responses

Forensic science international, 2023-08, Vol.349, p.111768-111768, Article 111768

2023

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A response to Marquis et al. (2017) What is the error margin of your signature analysis?

Forensic science international, 2018-06, Vol.287, p.e11-e12

2018

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INTERPOL SURVEY OF THE USE OF SPEAKER IDENTIFICATION BY LAW ENFORCEMENT AGENCIES

Forensic science international, 2016-06, Vol.263, p.92-100

2016

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The opacity myth: A response to Swofford & Champod (2022)

Forensic science international. Synergy, 2022-01, Vol.5, p.100275-100275, Article 100275

2022

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Vacuous standards – Subversion of the OSAC standards-development process

Forensic science international. Synergy, 2020-01, Vol.2, p.206-209

2020

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Forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios

Forensic science international. Synergy, 2022-01, Vol.5, p.100272-100272, Article 100272

2022

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Protocol for the collection of databases of recordings for forensic-voice-comparison research and practice

Australian journal of forensic sciences, 2012-06, Vol.44 (2), p.155-167

2012

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Validations of an alpha version of the E3 Forensic Speech Science System (E3FS3) core software tools

Forensic science international. Synergy, 2022-01, Vol.4, p.100223-100223, Article 100223

2022

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A strawman with machine learning for a brain: A response to Biedermann (2022) the strange persistence of (source) “identification” claims in forensic literature

Forensic science international. Synergy, 2022-01, Vol.4, p.100230-100230, Article 100230

2022

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A single test pair does not a method validation make: A response to Kirchhübel et al. (2023)

Science & justice, 2023-05, Vol.63 (3), p.327-329

Morrison, Geoffrey Stewart

2023

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A response to Busey & Klutzke (2022): Regarding subjective assignment of likelihood ratios

Science & justice, 2023-01, Vol.63 (1), p.61-62

Morrison, Geoffrey Stewart

2023

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Reply to Response to Vacuous standards – Subversion of the OSAC standards-development process

Forensic science international. Synergy, 2021-01, Vol.3, p.100149-100149, Article 100149

2021

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Testing theories of vowel inherent spectral change

The Journal of the Acoustical Society of America, 2007-07, Vol.122 (1), p.EL15-EL22

2007

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Measuring the validity and reliability of forensic likelihood-ratio systems

Science & justice, 2011-09, Vol.51 (3), p.91-98

Morrison, Geoffrey Stewart

2011

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Score based procedures for the calculation of forensic likelihood ratios – Scores should take account of both similarity and typicality

Science & justice, 2018-01, Vol.58 (1), p.47-58

2018

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Likelihood-ratio forensic voice comparison using parametric representations of the formant trajectories of diphthongs

The Journal of the Acoustical Society of America, 2009-04, Vol.125 (4), p.2387-2397

Morrison, Geoffrey Stewart

2009

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Vowel Inherent Spectral Change

An empirical estimate of the precision of likelihood ratios from a forensic-voice-comparison system

The impact in forensic voice comparison of lack of calibration and of mismatched conditions between the known-speaker recording and the relevant-population sample recordings

Tutorial on logistic-regression calibration and fusion:converting a score to a likelihood ratio

Admissibility of Forensic Voice Comparison Testimony in England and Wales

Advancing a paradigm shift in evaluation of forensic evidence: The rise of forensic data science

In the context of forensic casework, are there meaningful metrics of the degree of calibration?

Empirical test of the performance of an acoustic-phonetic approach to forensic voice comparison under conditions similar to those of a real case

Speaker identification in courtroom contexts – Part I: Individual listeners compared to forensic voice comparison based on automatic-speaker-recognition technology

Speaker identification in courtroom contexts – Part II: Investigation of bias in individual listeners’ responses

A response to Marquis et al. (2017) What is the error margin of your signature analysis?

INTERPOL SURVEY OF THE USE OF SPEAKER IDENTIFICATION BY LAW ENFORCEMENT AGENCIES

The opacity myth: A response to Swofford & Champod (2022)

Vacuous standards – Subversion of the OSAC standards-development process

Forensic comparison of fired cartridge cases: Feature-extraction methods for feature-based calculation of likelihood ratios

Protocol for the collection of databases of recordings for forensic-voice-comparison research and practice

Validations of an alpha version of the E3 Forensic Speech Science System (E3FS3) core software tools

A strawman with machine learning for a brain: A response to Biedermann (2022) the strange persistence of (source) “identification” claims in forensic literature

A single test pair does not a method validation make: A response to Kirchhübel et al. (2023)

A response to Busey & Klutzke (2022): Regarding subjective assignment of likelihood ratios

Reply to Response to Vacuous standards – Subversion of the OSAC standards-development process

Testing theories of vowel inherent spectral change

Measuring the validity and reliability of forensic likelihood-ratio systems

Score based procedures for the calculation of forensic likelihood ratios – Scores should take account of both similarity and typicality

Likelihood-ratio forensic voice comparison using parametric representations of the formant trajectories of diphthongs

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