| Summary: | The aim of this thesis is to provide guidance and information that will assist forensic speech scientists, and phoneticians generally, in making more accurate formant measurements, using commonly available speech analysis tools. Formant measurements are an important speech feature that are often examined in forensic casework, and are used widely in many other areas within the field of phonetics. However, the performance of software currently used by analysts has not been subject to detailed investigation. This thesis reports on a series of experiments that examine the influence that the analysis tools, analysis settings and speakers have on formant measurements. The influence of these three factors was assessed by examining formant measurement errors and their behaviour. This was done using both synthetic and real speech. The synthetic speech was generated with known formant values so that the measurement errors could be calculated precisely. To investigate the influence of different speakers on measurement performance, synthetic speakers were created with different third formant structures and with different glottal source signals. These speakers’ synthetic vowels were analysed using Praat’s normal formant measuring tool across a range of LPC orders. The real speech was from a subset of 186 speakers from the TIMIT corpus. The measurements from these speakers were compared with a set of hand-corrected reference formant values to establish the performance of four measurement tools across a range of analysis parameters and measurement strategies. The analysis of the measurement errors explored the relationships between the analysis tools, the analysis parameters and the speakers, and also examined how the errors varied over the vowel space. LPC order was found to have the greatest influence on the magnitude of the errors and their overall behaviour was closely associated with the underlying measurement process used by the tools. The performance of the formant trackers tended to be better than the simple Praat measuring tool, and allowing the LPC order to vary across tokens improved the performance for all tools. The performance was found to differ across speakers, and for each real speaker, the best performance was obtained when the measurements were made with a range of LPC orders, rather than being restricted to just one. The most significant guidance that arises from the results is that analysts should have an understanding of the basis of LPC analysis and know how it is applied to obtain formant measurements in the software that they use. They should also understand the influence of LPC order and the other analysis parameters concerning formant tracking. This will enable them to select the most appropriate settings and avoid making unreliable measurements.
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