Phoneme parameter extraction framework based on spectral and cepstral parameters is proposed. Using this framework, the phoneme signal is divided into frames and Hamming window is used. The performances are evaluated for recognition of Lithuanian vowel and semivowel phonemes. Different feature sets without noise as well as at different level of noise are considered. Two classical machine learning methods (Naive Bayes and Support Vector Machine) are used for classifying each problem, separately. The experiment results show that cepstral parameters give higher accuracies than spectral parameters. Moreover, cepstral parameters give better performance compared to spectral parameters in noisy conditions.
Authors
- Grazina Korvel,
- dr Olga Kurasova,
- prof. dr hab. inż. Bożena Kostek link open in new tab
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1007/978-3-319-98678-4_48
- Category
- Aktywność konferencyjna
- Type
- materiały konferencyjne indeksowane w Web of Science
- Language
- angielski
- Publication year
- 2018
