Identification of F1 and F2 in speech using modified zero frequency filtering
| Type of publication: | Conference paper |
| Citation: | Prasad_INTERSPEECH_2021 |
| Publication status: | Accepted |
| Booktitle: | Proceedings of Interspeech |
| Year: | 2021 |
| Abstract: | Formants are major resonances in the vocal tract system. Identification of formants is important for study of speech. In the literature, formants are typically identified by first deriving formant frequency candidates (e.g., using linear prediction) and then applying a tracking mechanism. In this paper, we propose a simple tracking-free formant identification approach based on zero frequency filtering. More precisely, formants F1-F2 are identified by modifying the trend removal operation in zero frequency filtering and picking simply the dominant peak in the short-term discrete Fourier transform spectra. We demonstrate the potential of the approach by comparing it against state-of-the-art formant identification approaches on a typical speech data set (TIMIT-VTR) and an atypical speech data set (PC-GITA). |
| Keywords: | atypical speech, Formant identification, Speech Analysis, Zero frequency filtering |
| Projects |
Idiap TIPS |
| Authors | |
| Added by: | [UNK] |
| Total mark: | 0 |
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