Normalizes acoustic vowel formant data using Lobanov Method.
norm.lobanov(vowels, f1.all.mean=NA, f2.all.mean=NA)a required dataframe of the format: speaker_id, vowel_id, context, F1, F2, F3, F1_glide, F2_glide, F3_glide. The context column and glide columns must exist but can be empty.
while it is not recommended that you supply values for f1.all.mean and f2.all.mean, doing so will override the speaker intrinsic generation of the mean formant values for the current speaker.
see above.
A data frame in the format: speaker_id, vowel_id, F1', F2', F1'gl, F2'gl, with the attributes "no.f3s" == TRUE, "norm.method" == "Lobanov"
The development of the library and this function are ongoing. The arguments to the function may change in future version.
Lobanov's method was one of the earlier vowel-extrinsic formulas to appear, but it remains among the best. The implementation here follows Nearey (1977) and Adank et al. (2004).
Thomas, Erik R. and Tyler Kendall. 2007. NORM: The vowel normalization and plotting suite. [ Online Resource: http://lingtools.uoregon.edu/norm/ ]
Adank, Patti, Smits, Roel, and van Hout, Roeland. 2004. A comparison of vowel normalization procedures for language variation research. Journal of the Acoustical Society of America 116:3099-107.
Lobanov, B. M. 1971. Classification of Russian vowels spoken by different listeners. Journal of the Acoustical Society of America 49:606-08.
Nearey, Terrance M. 1977. Phonetic Feature Systems for Vowels. Dissertation, University of Alberta. Reprinted 1978 by the Indiana University Linguistics Club.