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What does LTAS tell about the voice source?
Stockholm University, Faculty of Humanities, Department of Linguistics, Phonetics.ORCID iD: 0000-0002-1495-7773
2018 (English)In: 47th Annual Symposium: Care of the Professional Voice: Program Abstracts, 2018, p. 15-15Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Objective: The long-term-average spectrum, or LTAS has been extensively used in voice research. It provides an overall measure of voice characteristics allowing to derive a large number of parameters. A minimalistic set of parameters has been identified which offers the most essential properties [Eyben et al., 2015; 2016; Scherer et al., 2017]. LTAS analysis is typically applied to audio signals of running speech or continuous singing. It reflects the combination of formant frequency and voice source characteristics. Often, e.g. in clinical settings, it is relevant to distinguish between these two sources Voice source analysis can be performed by means of inverse filtering. The aim of the present work was to analyse the relationships between LTAS and voice source properties.

Method: Three internationally touring male singers sang scales in eleven different emotional colours. This material was analysed by inverse filtering as well as in terms of LTAS. The correlations between the averages across the scale tones of the flow glottogram parameters and minimalistic set of LTAS parameters were analysed.

Results/Conclusions: A strong negative correlation was found between spectral slope and the flow glottogram’s maximum flow declination rate MFDR, and a strong positive correlation between proportion of spectral energy below 1000Hz and H1-H2. Somewhat surprisingly, a strong negative correlation was found between equivalent sound level and the normalized and un-normalized amplitude quotients (the ratio between AC peak-to-peak amplitude of the flow glottogram and MFDR). Thus, these LTAS parameters seem particularly informative with respect to voice source characteristics.

Place, publisher, year, edition, pages
2018. p. 15-15
National Category
Signal Processing Music
Identifiers
URN: urn:nbn:se:su:diva-172820OAI: oai:DiVA.org:su-172820DiVA, id: diva2:1349995
Conference
47th Annual Symposium, Care of the Professional Voice, Philadelphia, USA, May 30 - June 3, 2018
Available from: 2019-09-10 Created: 2019-09-10 Last updated: 2019-09-23Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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