Identification of voices in disguised speech Jessica Clark* & Paul Foulkes** * University of York ** University of York & JP French Associates pf11@york.ac.uk.
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Identification of voices in disguised speech
Jessica Clark* & Paul Foulkes**
* University of York
** University of York & JP French Associates
pf11@york.ac.uk
IAFPA, Göteborg 2006
2
0.1 outline
• experiment to test ability of lay listeners to identify disguised familiar voices
• voices have been disguised artificially, as with commercially available voice changers– pitch modified
3
0.2 structure
1. introduction– rationale for experiment
2. experimental design– speakers– listeners– Control condition– Experimental conditions
3. results
4. discussion & conclusion
5
1. Introduction
• technical speaker identification is the most frequent task for the forensic phonetician
• lay identification is also common in legal cases
• many previous studies have thus examined lay listeners’ ability to identify voices and the factors which affect their ability
6
1.1 previous studies
• identification is not automatic or flawless
• listeners can make errors even with highly familiar voices – Ladefoged did not recognise his mother from a short
sample (Ladefoged & Ladefoged 1980)
– flatmates scored only 68% with 10 second samples (Foulkes & Barron 2000)
7
1.1 previous studies
• identification may be affected by [Bull & Clifford 1984]
– type of exposure (active/passive)– length of sample– nature of sample (phone, direct, shouting etc)– delay between exposure and test– age of listener– hearing ability– sightedness– natural variability across individual listeners– specific features of voice– degree of familiarity– nature and extent of any disguise
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1.2 degree of familiarity
• all things equal, more familiar voices are easier to identify
• e.g. Hollien, Majewski & Doherty (1982)– listening tests with 10 male voices
listener group N % correct
(normal condition)
familiar 10 98
trained 47 40
unfamiliar 14 27
9
1.3 disguise
• all things equal, disguised voices are harder to identify
• e.g. Hollien, Majewski & Doherty (1982)– various forms of disguise used
listener group N % correct (normal)
% correct (disguised)
familiar 10 98 79
trained 47 40 21
unfamiliar 14 27 18
machine approach (LTAS) 30
10
1.3 disguise
• previous studies have examined various types of disguise– whisper, pencils between teeth, hypernasality,
dialect change, rate change, professional mimics
• but little if any work on voice changers– hardware based– software based– easily available
12
1.3 disguise
• in our study we chose not to use real voice changers, in favour of total control over effects
• pitch shift chosen as a universal function
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2.1 design outline
• simple design
• listeners asked to identify samples of familiar voices
• Control condition unmodified stimuli
• 4 Experimental conditions modified stimuli
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2.1 design outline
• degree of familiarity known to affect rate of successful identification
• thus we trained listeners to identify a group of speakers– controls degree of familiarity– all listeners had exactly the same exposure in terms
of length & quality of samples– identification task carried out under same conditions
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2.2 speakers
• 4 male speakers– 16-18 years old
• taken from IViE corpus (Grabe, Post & Nolan 2001)
– Leeds dialect (nearest to York)– reading text of Cinderella story
IViE speaker Experimental name
JP Edward
JW Matthew
MD Harry
RP David
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2.2 speakers
• training materials created for each speaker– c. 90 seconds of Cinderella (302 words)– edited out disfluencies, non-speech sounds, long
pauses– samples normalised for amplitude with Audacity
1.2.5
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2.3 listeners
• 36 listeners• variety of regional/social backgrounds• York residents• age range 19-55• 10 male, 26 female
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2.4 Control condition
• all 36 listeners – 4 voices * 90 seconds = c. 6 minutes
– presented by PowerPoint with speakers’ names
– Toshiba laptop– Aiwa A170 headphones– individually in quiet room
1. training phase
2. break
3. listening test
2.4 Control condition
• all 36 listeners
– 8 stimuli (2 per
speaker)– duration c. 10 seconds– 5 second gap between– extracts from other parts
of Cinderella story– normalised for amplitude
with Audacity 1.2.5– answer sheet with names
1. training phase
2. break
3. listening test
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2.5 Experimental conditions
• 4 Experimental conditions
• listening tests same format as Control condition
• but stimuli modified for pitch
• Sound Forge 8.0– pitch shift effect– accuracy setting ‘high’– speech 1 mode– preserved durations
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2.5 Experimental conditions
(i) +8 semitones
(ii) +4 semitones
(iii) -4 semitones
(iv) -8 semitones
pitch shift > 8 semitones unnatural and partly incomprehensible
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2.5 Experimental conditions
• listening test 16-92 days after Control test– no clear effects for length of delay
• same training as in Control condition• 10 minute break• 2 stimuli for familiarisation
• 8 experimental stimuli per condition– consecutive runs for + and - stimuli
– order reversed for half of each group, but no effect
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3.1 Control condition
• average correct identification = 4.8/8 (60%)
0
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5
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Minus 8 Minus 4 Control Plus 4 Plus 8
ave
rag
e N
co
rre
ct
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3.1 Control condition
• individuals’ range 8 to 0• 29/36 performed better than chance
control
0
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2
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listeners
N c
orr
ect
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3.2 Experimental conditions
• ** sig. lower than in Control (p < .005, Wilcoxon)
• trend (n.s.) for higher scores in + conditions
0
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Minus 8 Minus 4 Control Plus 4 Plus 8
ave
rag
e N
co
rre
ct
** ******
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-8 semitones
0
1
2
3
4
5
6
7
8
listeners
N c
orr
ect
+8 semitones
0
1
2
3
4
5
6
7
8
listeners
N c
orr
ect
+4 semitones
0
1
2
3
4
5
6
7
8
listeners
N c
orr
ect
-4 semitones
0
1
2
3
4
5
6
7
8
listeners
N c
orr
ect
• variability in listener performance, esp. ±4• majority perform above chance except -8
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3.3 variation by listener sex
• women sig. better in Control (p = .008, Mann-Whitney)
– trend (n.s.) maintained in Experimental tests– same pattern reported by Bull & Clifford (1984)
0
1
2
3
4
5
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7
8
Minus 8 Minus 4 Control Plus 4 Plus 8
N c
orr
ec
t
Male Female
**
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3.4 summary
• as predicted, identification rates were lower with disguised voices– lowest scores with most extreme form of disguise
(±8 semitones)
• identification rates slightly better when pitch shifted up than down
• trend for women to perform better than men
• variability across listeners
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4. discussion & conclusion
• tests reported here were not forensically realistic
• results may be affected by e.g.– degree of familiarity with voice– content of sample (vocabulary, syntax etc)– conditions of exposure (stress etc)– specific form of artificial disguise
• software, hardware system• combination of effects
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4. discussion & conclusion
• considerable variation in listeners’ scores– courts should not assume all witnesses are equally
good at such tasks– supports broader principle that lay witnesses should
be tested in their ability to identify a voice
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4. discussion & conclusion
• but even marked disguise was not catastrophic for listeners
• a broadly positive conclusion for lay speaker identification– a reasonable chance of identifying familiar voices
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4. discussion & conclusion
• but a less positive conclusion respect to use of voice changers as a means of protecting vulnerable witnesses giving evidence
• more extreme forms of modification may affect intelligibility & naturalness
• less extreme forms of modification may render witness’s voice recognisable
• different modifications for different voices?
40
References
Bull, R. & Clifford, B. (1984) Earwitness voice recognition accuracy. In G. Wells & E. Loftus (eds.) Eyewitness Testimony: Psychological Perspectives. Cambridge: CUP. pp. 92-123.
Foulkes, P. & Barron, A. (2000) Telephone speaker recognition amongst members of a close social network. Forensic Linguistics 7: 181-198.
Grabe, E., Post, B. & Nolan, F. (2001) English intonation in the British Isles: the IViE corpus. Final report to UK ESRC R000 237145. www.phon.ox.ac.uk/IViE
Hollien, H., Majewski, W. & Doherty, E. (1982) Perceptual identification of voices under normal, stress and disguise speaking conditions. Journal of Phonetics 10: 139-148.
Ladefoged, P. & Ladefoged, J. (1980) The ability of listeners to identify voices. UCLA Working Papers in Phonetics 49: 43-51.
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