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Ferrer, L.; Bratt, H.; Richey, C.; Franco, H.; Abrash, V.; Precoda, K. "Lexical stress classification for language learning using spectral and segmental features" (2014) 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014:7704-7708
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Abstract:

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, spectral tilt and duration measurements. The spectral features are computed at the frame level and are modeled by one Gaussian Mixture Model (GMM) for each stress class. These GMMs are used to obtain segmental posteriors, which are then appended to the segmental features to obtain a final set of GMMs. The segmental GMMs are used to obtain posteriors for each stress class. The system was tested on English speech from native English-speaking children and from Japanese-speaking children with variable levels of English proficiency. Our algorithm results in an error rate of approximately 13% on native data and 20% on Japanese non-native data. © 2014 IEEE.

Registro:

Documento: Conferencia
Título:Lexical stress classification for language learning using spectral and segmental features
Autor:Ferrer, L.; Bratt, H.; Richey, C.; Franco, H.; Abrash, V.; Precoda, K.
Ciudad:Florence
Filiación:Speech Technology and Research Laboratory, SRI International, CA, United States
CONICET, Argentina
Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina
Palabras clave: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
Año:2014
Página de inicio:7704
Página de fin:7708
DOI: http://dx.doi.org/10.1109/ICASSP.2014.6855099
Título revista:2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014
Título revista abreviado:ICASSP IEEE Int Conf Acoust Speech Signal Process Proc
ISSN:15206149
CODEN:IPROD
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_15206149_v_n_p7704_Ferrer

Referencias:

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  • Franco, H., Bratt, H., Rossier, R., Gadde, V.R., Shriberg, E., Abrash, V., Precoda, K., EduSpeak: A speech recognition and pronunciation scoring toolkit for computeraided language learning applications (2010) Language Testing, 27 (3), pp. 401-418. , July
  • Talkin, D., (1995) Robust Algorithm for Pitch Tracking, , Elsevier Science
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Citas:

---------- APA ----------
Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V. & Precoda, K. (2014) . Lexical stress classification for language learning using spectral and segmental features. 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, 7704-7708.
http://dx.doi.org/10.1109/ICASSP.2014.6855099
---------- CHICAGO ----------
Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V., Precoda, K. "Lexical stress classification for language learning using spectral and segmental features" . 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 (2014) : 7704-7708.
http://dx.doi.org/10.1109/ICASSP.2014.6855099
---------- MLA ----------
Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V., Precoda, K. "Lexical stress classification for language learning using spectral and segmental features" . 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014, 2014, pp. 7704-7708.
http://dx.doi.org/10.1109/ICASSP.2014.6855099
---------- VANCOUVER ----------
Ferrer, L., Bratt, H., Richey, C., Franco, H., Abrash, V., Precoda, K. Lexical stress classification for language learning using spectral and segmental features. ICASSP IEEE Int Conf Acoust Speech Signal Process Proc. 2014:7704-7708.
http://dx.doi.org/10.1109/ICASSP.2014.6855099