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Current trends in sociophonetic data analysis indicate a shift to entirely automatic measurements of spectral properties using programs like Praat. While such practices are useful for the rapid collection of acoustic data from large corpora, they, by default do not permit human analysts to provide quality control or make hand corrected measurements when needed. Under ideal signal-to-noise conditions, such as in a sound-proof room, this may not be a problem. However, analysis of audio recordings made in acoustically-uncontrolled environments, like many standard sociolinguistic interviews, are arguably susceptible to spurious estimates using automated routines. This paper presents the results of a highly controlled noise-interference experiment designed to examine the effects of different types of noise at varying signal-to-noise levels on automated LPC-based vowel formant measurements made in Praat. Findings indicate that some noises are more detrimental than others, affect some formant frequencies more than others and that louder noises make it inappropriate to conduct an analysis of F1 and F2. Results are discussed and suggestions for better practices in recording sociolinguistic interviews for sociophonetic data collection are presented.

An evaluation of noise on LPC-based vowel formant estimates: Implications for sociolinguistic data collection