Accrediting a small Forensic Speaker Comparison Lab Text Jonas - - PowerPoint PPT Presentation

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Accrediting a small Forensic Speaker Comparison Lab Text Jonas - - PowerPoint PPT Presentation

Jun 15, 2023 233 likes •384 views

Accrediting a small Forensic Speaker Comparison Lab Text Jonas Lindh Forensic Phonetic Analyst Voxalys AB University of Gothenburg Department of Clinical Neuroscience Sahlgrenska Academy University of Gothenburg 1 Voxalys AB

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Accrediting a small Forensic Speaker Comparison Lab

Jonas Lindh Forensic Phonetic Analyst Voxalys AB University of Gothenburg Department of Clinical Neuroscience Sahlgrenska Academy University of Gothenburg

Text 1

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2

Voxalys AB

  • Performed casework for 11 years
  • Sweden, Norway and US
  • approximately 400 cases
  • 3 employees part time (also

employed at the university)

  • Subcontractor of NFC (National

Forensic Centre, Sweden)

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3

Outline

  • Applied methods
  • Evaluations for accreditation
  • Forensic Conclusions in Sweden
  • Inference?
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4

3 part casework analysis

  • NFC screening, in-house screening, punting

samples during analysis…

  • Part 1 - Linguistic phonetic perceptual

analyses (FSASR)

  • blind testing
  • Part 2 - Acoustic measurement AR, F0 &

LTF (FSASR)

  • Part 3 - AVC, Automatic Voice Comparison

(FASR) (2 systems active, 1 evaluating, 1 for research)

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5

Evaluations for accreditation

  • Guidelines
  • Drygajlo, A., Jessen, M., Gfroerer, S., Wagner, I.,

Vermeulen, J., Niemi, T., 2015. Methodological Guidelines for best practice in forensic semiautomatic and automatic speaker recognition, including guidance

  • n the conduct of proficiency testing and collaborative
  • exercises. Wiesbaden, Germany. European Network of

Forensic Science Institutes.

  • Meuwly, D., Ramos, D., Haraksim, R., A guideline for

the validation of likelihood ratio methods used for forensic evidence evaluation, Forensic Sci. Int. (2016), http://dx.doi.org/10.1016/j.forsciint.2016.03.048

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6

Evaluations for accreditation

  • 6
  • 4
  • 2
2 4 6 logit prior 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 pError logLRs LR values After PAV LR=1 always 0.1 0.2 0.3 0.4 0.5 0.6

Cllr [bits] discrimination loss calibration loss 0.1 0.2 0.5 1 2 5 10 20 40 False Alarm probability (in %) 0.1 0.2 0.5 1 2 5 10 20 40 Miss probability (in %)

DET plot

DET curve
  • 2.5
  • 2
  • 1.5
  • 1
  • 0.5
0.5 1 1.5 2 2.5

Prior log10(odds)

0.1 0.2 0.3 0.4 0.5

logLRs LR values After PAV LR=1 always

  • 6
  • 5
  • 4
  • 3
  • 2
  • 1
1 2 3

log10LRs

0.02 0.04 0.06 0.08 0.1

Normalized count Hp true Hd true

  • 3
  • 2
  • 1

1 2 3

Log10(LR) Greater Than

20 40 60 80 100

Proportion of cases (%) Hp Bound Hd Bound logLRs

  • 10
  • 8
  • 6
  • 4
  • 2
2 4 6 8 10

logit :

0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2

normalized Bayes error-rate Likelihood Ratios log LR = 0 Emin true log LR 30 false alarms 30 misses

  • 6
  • 5
  • 4
  • 3
  • 2
  • 1
1 2 3

log10LR

10 20 30 40 50 60 70 80 90 100

Proportion of cases (%) Tippett plot 1 Hp true Hd true

  • 6
  • 5
  • 4
  • 3
  • 2
  • 1
1 2 3

log10LR

10 20 30 40 50 60 70 80 90 100

Proportion of cases (%) Tippett plot 2 Hp true Hd true

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Evaluations for accreditation

  • GSM-GSM performance durations

CLLRmins 1x10 1x20 2x10 1x30 3x10 1x40 2x20 4x10 1x50 5x10 1x60 2x30 3x20 6x10 1x70 7x10 1x80 2x40 4x20 8x10 1x90 3x30 9x10 1x100 2x50 5x20 10x10 1x110 11x10 1x120 2x60 3x40 4x30 6x20 12x10 10s

,573 ,557 ,495 ,532 ,428 ,481 ,430 ,425 ,460 ,413 ,435 ,393 ,342 ,324 ,395 ,329 ,401 ,341 ,314 ,366 ,394 ,327 ,300 ,403 ,327 ,284 ,293 ,368 ,257 ,212 ,319 ,326 ,325 ,281 ,287

20s

,495 ,457 ,400 ,444 ,318 ,404 ,312 ,288 ,345 ,284 ,334 ,285 ,245 ,219 ,301 ,212 ,299 ,243 ,220 ,232 ,290 ,234 ,210 ,299 ,215 ,193 ,201 ,268 ,151 ,273 ,217 ,226 ,224 ,195 ,163

30s

,544 ,394 ,351 ,397 ,263 ,373 ,256 ,234 ,300 ,236 ,279 ,224 ,199 ,175 ,268 ,152 ,258 ,196 ,173 ,195 ,246 ,172 ,159 ,270 ,190 ,157 ,160 ,236 ,117 ,235 ,175 ,197 ,176 ,156 ,142

40s

,438 ,382 ,338 ,362 ,234 ,350 ,258 ,215 ,261 ,209 ,235 ,207 ,194 ,132 ,214 ,113 ,214 ,173 ,162 ,160 ,204 ,152 ,142 ,231 ,145 ,162 ,147 ,214 ,107 ,201 ,150 ,172 ,151 ,148 ,122

50s

,380 ,320 ,300 ,304 ,180 ,327 ,192 ,168 ,212 ,168 ,190 ,156 ,130 ,083 ,190 ,104 ,200 ,143 ,101 ,096 ,175 ,101 ,088 ,215 ,121 ,105 ,084 ,193 ,068 ,187 ,125 ,137 ,089 ,079 ,075

60s

,370 ,339 ,293 ,290 ,198 ,327 ,200 ,159 ,204 ,167 ,186 ,149 ,137 ,082 ,153 ,105 ,184 ,123 ,119 ,069 ,168 ,074 ,097 ,206 ,095 ,108 ,091 ,176 ,083 ,161 ,106 ,129 ,068 ,086 ,094

70s

,420 ,311 ,295 ,281 ,210 ,305 ,194 ,161 ,213 ,153 ,178 ,145 ,123 ,068 ,161 ,124 ,156 ,131 ,120 ,077 ,135 ,091 ,090 ,169 ,109 ,115 ,087 ,164 ,081 ,154 ,104 ,121 ,070 ,087 ,090

80s

,434 ,300 ,341 ,244 ,206 ,295 ,185 ,154 ,184 ,149 ,152 ,122 ,104 ,062 ,145 ,096 ,142 ,105 ,071 ,074 ,122 ,068 ,054 ,145 ,075 ,078 ,028 ,126 ,024 ,132 ,064 ,094 ,056 ,053 ,031

90s

,370 ,278 ,337 ,243 ,155 ,300 ,177 ,140 ,181 ,132 ,141 ,126 ,100 ,048 ,118 ,085 ,121 ,106 ,070 ,076 ,117 ,069 ,049 ,144 ,074 ,083 ,025 ,104 ,024 ,128 ,065 ,093 ,056 ,049 ,022

100s

,339 ,278 ,270 ,254 ,118 ,242 ,130 ,081 ,178 ,099 ,143 ,128 ,077 ,053 ,125 ,068 ,123 ,113 ,058 ,020 ,094 ,068 ,018 ,127 ,067 ,077 ,032 ,109 ,014 ,113 ,067 ,094 ,060 ,032 ,023

110s

,283 ,261 ,230 ,241 ,100 ,203 ,077 ,062 ,138 ,067 ,110 ,101 ,073 ,046 ,107 ,052 ,127 ,101 ,053 ,003 ,087 ,061 ,013 ,106 ,055 ,094 ,020 ,080 ,010 ,124 ,051 ,090 ,060 ,023 ,024

120s

,280 ,236 ,248 ,233 ,087 ,218 ,077 ,061 ,127 ,075 ,096 ,092 ,074 ,026 ,079 ,051 ,115 ,095
  • ,003
,074 ,061 ,007 ,075 ,046 ,094 ,014 ,068 ,006 ,099 ,037 ,078 ,051 ,020 ,020
  • from “FRITS” - David van der Vloed

at NFI

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Evaluations for accreditation

  • Microphone (Olympus dictaphone

recordings and Zoom H4) vs GSM

  • Microphone vs microphone (short or long

distance with room acoustics)

  • Mobile video recordings vs GSM and/or

Mic

  • With and without face cover
  • In and outside car
  • Indoor and outdoor
  • Different languages
  • Compressions (DSS, MP3, WMV, AMR,

3GP, Speex) 128kbps ->8kbps

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Evaluations for accreditation

  • Perceptual phonetic analysis
  • Training, testing -> Evaluation blind
  • small scale - very time consuming
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Conclusions in Sweden

  • National Forensic Centre (NFC)

uses 2 hypotheses and a 9 point

  • rdinal scale with verbal

expressions

  • Level +4 …the results are extremely much more

probable if the main hypothesis is true compared to if the alternative hypothesis is true.

  • Level -2 …the results are more probable if the

alternative hypothesis is true compared to if the main hypothesis is true. Behind each level is a span of likelihood ratios…

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Inference

  • Every case is unique…
  • How much can you infer from

evaluations to an actual case?

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General questions

  • What does it mean to have a

transparent report?

  • Who has to be able to understand

it?

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Thank you for the attention!

http://www.voxalys.se http://www.ling.gu.se/~jonas