Classification of lexical stress using spectral and prosodic features for computer-assisted language learning systems

We present a system for detection of lexical stress in English words spoken by English learners. This system was designed to be part of the EduSpeak® computer-assisted language learning (CALL) software. The system uses both prosodic and spectral features to detect the level of stress (unstressed, pr...

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Detalles Bibliográficos
Autores principales: Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V., Precoda, K.
Formato: JOUR
Materias:
Computer-assisted language learning
Gaussian mixture models
Lexical stress detection
Mel frequency cepstral coefficients
Prosodic features
Computational linguistics
Computer aided instruction
Consumer products
E-learning
Feature extraction
Linguistics
Probability
Speech recognition
Computer assisted language learning
Gaussian Mixture Model
Mel frequency cepstral co-efficient
Stress detection
Learning systems
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01676393_v69_n_p31_Ferrer
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires

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