Lexical stress classification for language learning using spectral and segmental features

We present a system for detecting lexical stress in English words spoken by English learners. The system uses both spectral and segmental features to detect three levels of stress for each syllable in a word. The segmental features are computed on the vowels and include normalized energy, pitch, spe...

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Detalles Bibliográficos
Autores principales: Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V., Precoda, K.
Formato: CONF
Materias:
Computer-aided language learning
Gaussian Mixture Models
Stress classification
Communication channels (information theory)
Computer aided instruction
Object recognition
Computer-Aided Language Learning
English word
Gaussian Mixture Model
Language learning
Non-native
Spectral feature
Spectral tilt
Stress classifications
Signal processing
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_15206149_v_n_p7704_Ferrer
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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