1. Philip Harrison J P French Associates & Department of Language & Linguistic Science, York University IAFPA 2006 Annual Conference Göteborg, Sweden Variability of Formant Measurements – Part 2

2. l 2 Summary Briefly recap previous analysis & last year’s presentation New analysis & results PhD research Questions

3. l 3 Study Aim: Investigate the variability of formant measurements which exists both within and between different software programs currently used in the field of forensic phonetics. –3 programs – Praat, Multispeech & Wavesurfer –3 analysis parameters – LPC order, analysis (frame/window) width, pre-emphasis –Word list – 5 vowel categories – 6 tokens per category – read 3 times – total = 90 tokens –2 speakers – Peter French & me –2 simultaneous recordings – microphone & telephone

4. l 4 Results & Analysis Scripts used to obtain 37,260 individual formant measurements using LPC formant trackers Analysis – microphone data only –Initial observations of raw formant data –Quantitative analysis of results –Statistical analysis

5. l 5 My F1s from Praat LPC Variation FLEECETRAPPALMGOOSESCHWA

6. l 6 The Plot Shows… Scripts work – (used in fault finding) Vowel categories clear Greatest deviation – LPC orders 6 & 8 Orders 10 to 18 very similar for FLEECE, GOOSE & SCHWA Generated many more plots for all formants, parameters & software –Lots of variation –Difficult to interpret

7. l 7 Quantitative Analysis Quantitative Difference Analysis –No absolute measurement to compare formants with – outcome of analysis, not directly comparable with acoustic reality –Difference calculated between value obtained with default analysis settings –Absolute difference calculated for each formant then averaged by vowel category –Shows variation between two analyses

8. l 8 Observations Numerical analysis confirmed impression from plots Clear differences between vowel categories, speakers, formants, software & settings Complex set of results with no clear patterns

9. l 9 Statistical Analysis Paired t-test between measurements from default settings and varied settings for each vowel category –Null hypothesis – altering analysis settings  no effect –Exp hypothesis – altering analysis settings  effect Number of significant ‘hits’ summed – max 15 Higher number = greater variation in formant measurements 2 significance levels – 0.01 & 0.05

10. l 10 Conclusions Hoped to have clear patterns, able to produce set of guidelines/recommendations Patterns only at specific, detailed level Very clear that many factors affect formant measurements No software is obviously better than others Care should be taken when measuring formants

11. l 11 New Work!!! Initial data contained obviously incorrect measurements Discard measurements – criterion? Determine acceptable band –Spectrograms – no –Formant bandwidths – no (attempted) –LPC tracker & spectrogram – no (attempted) –Spectrum of selection – yes but still encountered problems Band limit 300 Hz – impressionistic

12. l 12 Spectrum Measurements Used to determine centre of 300 Hz acceptable band Spectrum with 260 Hz bandwidth – same as default spectrogram Measured peaks F1, F2 & F3 Issues/problems –Windowed -> biased to centre of selection –Formant peaks not always clear – some tokens ignored –Double peaks – highest peak measured

13. l 13 Analysis of Accepted Measurements Analyse LPC variation only – other parameters more stable – not altered No accurate reference which raw measurements can be judged against Accepted results provide indication of accuracy & consistency Clear patterns in accepted formants Condense results – % accepted per vowel category

14. l 14 Plot of Accepted Results

15. l 15 Me Microphone Accepted PraatMultispeechWavesurfer F1 F2 F3

16. l 16 Me Telephone Accepted PraatMultispeechWavesurfer F1 F2 F3

17. l 17 JPF Microphone Accepted PraatMultispeechWavesurfer F1 F2 F3

18. l 18 JPF Telephone Accepted PraatMultispeechWavesurfer F1 F2 F3

19. l 19 General Patterns Praat & Multispeech – bell curves –Most consistent setting – P 10, MS 10 to 14 –Curves shifted to left (lower LPC) for phone Wavesurfer – horizontal –Different behaviour to Praat & Multispeech –Some very weak results – especially F3 –For me better results for phone recording (also true for Praat & Multispeech) Most consistent setting Praat LPC 10 Again variation across vowel category, speaker, formant, software & condition

20. l 20 Microphone vs Telephone Künzel (2001): –Landline phone vs microphone –Largest F1 difference in region of 14% for close vowels Byrne & Foulkes (2004): –GSM mobile phone vs microphone –F1 average 29% higher for GSM Not big differences for F2 & F3 Current data (spectral comparisons) – only 2 speakers

21. l 21 Comparison Tables Me JPF

22. l 22 General Observations LPC tracks for phone recordings more stable, easier to measure –Less ‘information’ above F3 –Possibly pre-filter recordings? Different LPC orders produce better tracks for different formants of the same token –Contradicts my previous advice to keep LPC setting constant across vowel categories

23. l 23 PhD Next Steps Use synthesised speech Formant values specified Repeat software experiments Other factors to investigate –Pitch –Voice quality –Interaction of analysis parameters

24. l 24 Other Potential Areas of Investigation for PhD Effects of GSM coding & transmission Acoustic environments Pseudo-formants – source??? Mouth/telephone distance & orientation Any other ideas…?

25. l 25 Questions ? Thanks to Peter French & Paul Foulkes