The aim of the current study is to propose acoustic features for detection
of nasals in continuous speech. Acoustic features that represent certain
characteristics of speech production are extracted. Features representing
excitation source characteristics are extracted using zero frequency
filtering method. Features representing vocal tract system characteristics
are extracted using zero time windowing method.
Feature sets are formed
by combining certain subsets of the features mentioned above. These
feature sets are evaluated for their representativeness of nasals in
continuous speech in three different languages, namely, English, Hindi
and Telugu. Results show that nasal detection is reliable and consistent
across all the languages mentioned above.
Cite as: Nellore, B.T., Dumpala, S.H., Nathwani, K., Gangashetty, S.V. (2019) Excitation Source and Vocal Tract System Based Acoustic Features for Detection of Nasals in Continuous Speech. Proc. Interspeech 2019, 166-170, doi: 10.21437/Interspeech.2019-2785
@inproceedings{nellore19_interspeech, author={Bhanu Teja Nellore and Sri Harsha Dumpala and Karan Nathwani and Suryakanth V. Gangashetty}, title={{Excitation Source and Vocal Tract System Based Acoustic Features for Detection of Nasals in Continuous Speech}}, year=2019, booktitle={Proc. Interspeech 2019}, pages={166--170}, doi={10.21437/Interspeech.2019-2785} }