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Automatic estimation of the first subglottal resonance.
Harish Arsikere1, Steven M Lulich, Abeer Alwan
1Department of Electrical Engineering, University of California, Los Angeles, California 90095, USA. harishan@ucla.edu
The Journal of the Acoustical Society of America
|May 17, 2011
Summary
This study introduces a new method for automatically estimating the first subglottal resonance (Sg1) using speech data. The technique accurately predicts Sg1 in both English and Spanish, offering a valuable tool for speech analysis.
Area of Science:
- Speech Science
- Acoustic Phonetics
- Bioacoustics
Background:
- The first subglottal resonance (Sg1) is crucial for understanding voice production.
- Accurate estimation of Sg1 is challenging, often requiring invasive or complex methods.
Purpose of the Study:
- To develop and validate an automatic method for estimating the first subglottal resonance (Sg1).
- To establish an empirical relationship for Sg1 estimation using speech parameters.
Main Methods:
- Collected speech and subglottal data from native American English and bilingual Spanish/English speakers.
- Derived an empirical relation between the first formant frequency, fundamental frequency, and Sg1.
- Validated the automatic Sg1 estimation on voiced sounds from English and Spanish sentences.
Main Results:
- An empirical relation was successfully derived from 11 speakers.
- Automatic Sg1 estimation was performed on data from 22 speakers.
- The average error in estimating Sg1 was less than 50 Hz.
Conclusions:
- The developed method provides accurate automatic estimation of Sg1.
- This technique is effective for both English and Spanish speech.
- The findings offer a non-invasive approach to Sg1 analysis in speech research.
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