A Study on the Importance of Formant Transitions for Stop-Consonant Classification in VCV Sequence
| Type of publication: | Conference paper |
| Citation: | Chandrasekar_INTERSPEECH_2023 |
| Publication status: | Accepted |
| Booktitle: | Interspeech |
| Year: | 2023 |
| Month: | August |
| Publisher: | ISCA |
| Location: | Dublin, Ireland |
| Abstract: | This study analyzes formant transitions in six English stop-consonants in vowel-consonant-vowel (VCV) sequences. We investigate whether natural speech preserves formant patterns, and if not, how it affects stop-consonant perception and automatic classification. We specifically ask three questions: 1) To what extent these formant transition patterns are preserved in naturally produced VCV sequences? 2) If not preserved, does it have any effect on the perception of the stop-consonant? 3) How does the classification of stop-consonants by automatic classifiers change when formant transition patterns are not preserved? We found that 33.56% of the corpus deviate from the formant transition pattern. The perception test reveals an Unweighted Average Recall (UAR) of 91.97% in identifying the stop-consonants in the VCV sequences when the pattern is not preserved compared to 93.54% when it is preserved. The best UAR from an automatic classifier is 68.35% and 77.5% in these two cases, respectively. |
| Keywords: | Formant transitions, Speech Analysis, Stop-consonants |
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| Added by: | [UNK] |
| Total mark: | 0 |
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