Affective State and Voice: The Specific Properties of Overtone Distributions

Motivated by psychiatric interests and as part of our investigations into the basic properties of human speech, we carried out a normative study with 192 healthy subjects - stratified according to sex, age and education - in order to derive reference values of the general population and to learn to distinguish between normal fluctuations and significant changes over time. In the present investigation, our interest focused on the individual sound characteristics of speakers (“timbre”) rather than on speech behavior. Accordingly, we determined the optimum parameter setting for a problem-specific, reliable estimation of time dependent spectra. An interval of one second length was found to be optimum for reproducibly assessing formants and corresponding band-widths for more than 95% of the cases. Based on these findings, we adapted the concept of “spectral patterns” to speech analysis. It turned out that spectral voice patterns are stable over time and measure the fine graduations of mutual differences between human voices. A highly reliable computerized recognition of persons was possible by means of these quantities, on the basis of 16-32 s time series: 93% of persons could be uniquely recognized after a 14-day interval. Hence, we succeeded in developing specific means for modelling intra-individual changes of voice timbres over time. This is of particular interest for investigations of the speech characteristics of affectively disturbed patients, since the tonal expressiveness of human voices, or the lack thereof, essentially depends on the actual distribution of overtones and the corresponding variabilities.

Key-words

Formant Extraction - Spectral Voice Patterns - Computerized Recognition

• REFERENCES

• 1 Markel JD, Oshika BT, Gray AH. Long-term feature averaging for speaker recognition. IEEE Trans ASSP 1977; 25: 330-7.
• 2 Sambur MR. Selection of acoustic features for speaker identification. IEEE Trans ASSP 1975; 23: 176-82.
• 3 Wolf JJ. Efficient acoustic parameters for speaker recognition. J Acoust Soc Amer 1972; 51: 2044-55.
• 4 Yannakoudakis EJ, Hutton PJ. Speech Synthesis and Recognition Systems. Chichester: Ellis Horwood; 1987
• 5 Atal BS. Automatic recognition of speakers from their voices. Proc IEEE 1976; 64: 460-75.
• 6 Rosenberg AE, Shipley KL. Speaker identification and verification combined with speaker-independent word recognition. IEEE Conf ASSP 1981; 184-7.
• 7 Clemmer EJ. Psycholinguistic aspects of pauses and temporal patterns in schizophrenic speech. J Psycholinguist Res 1980; 09: 161-85.
• 8 Darby JK. Speech Evaluation in Psychiatry. New York: Grune and Stratton Inc; 1982
• 9 Darby JK, Sherk A. Speech studies in psychiatric populations. In: Hollien H, Hollien P. eds. Amsterdam Studies in the Theory and History of Linguistic Science (vol IV, 9, part II). 1979: 599-608.
• 10 Hargreaves WA, Starkweather JA, Blaker KH. Voice quality changes in depression. J Abnorm Psychol 1965; 70: 218-20.
• 11 Hollien H, Darby JK. Acoustic comparisons of psychotic and non-psychotic voices. In: Hollien H, Hollien P. eds. Amsterdam Studies in the Theory and History of Linguistic Science (vol IV, 9, part II). 1979: 609-14.
• 12 Nilsonne A. Acoustic analysis of speech variables during depression and after improvement. Acta Psychiat Scand 1987; 76: 234-45.
• 13 Nilsonne A. Speech parameters as indicators of depressive illness. Acta Psychiat Scand 1988; 77: 253-63.
• 14 Stassen HH, Bomben G. Affective state and voice: Reproducibility and sensitivity of speech parameters. Meth Inform 1988; 27: 87-96.
• 15 Stassen HH. Modeling affect in terms of speech parameters. Psychopathol 1988; 21: 83-8.
• 16 Stassen HH, Kuny S, Woggon B, Angst J. Affective state and voice: Results of a pilot study with six depressive patients. Pharmacopsychiatry 1988; 22: 17-22.
• 17 Stassen HH, Bomben G, Günther E. Speech characteristics in depression. (submitted for publication)
• 18 Stassen HH. The similarity approach to EEG analysis. Meth Inform Med 1985; 23: 200-12.
• 19 Stassen HH, Lykken DT, Propping P, Bomben G. Genetic determination of the human EEG, survey of recent results on twins reared together and apart. Hum Genet 1988; 80: 165-76.
• 20 Ruske G. Auditory perception and its application to computer analysis of speech. In: Fu KS. ed. Applications of Pattern Recognition (Vol 2, Auditory Signals). Boca Raton Fla: CRC Press; 1982: 1-39.