CONF Chandrasekar_INTERSPEECH_2023/IDIAP A Study on the Importance of Formant Transitions for Stop-Consonant Classification in VCV Sequence Chandrasekar, Siddarth Ramesh, Arvind Purohit, Tilak Ghosh, Prasanta Kumar Formant transitions Speech Analysis Stop-consonants EXTERNAL http://publications.idiap.ch/attachments/papers/2023/Chandrasekar_INTERSPEECH_2023.pdf PUBLIC Proceedings of Interspeech Dublin, Ireland 2023 ISCA 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.