Universal attribute characterization of spoken languages for automatic spoken language recognition

Computer Speech and Language

Volumn 27, Issue 1, 2013, Pages 209-227

  Siniscalchi, Sabato Marco ^a   Reed, Jeremy ^b   Svendsen, Torbjorn ^c   Lee, Chin Hui ^d  

^a KORE UNIVERSITY OF ENNA   (Italy)

^b GEORGIA TECH RESEARCH INSTITUTE   (United States)

^c NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^d GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Artificial neural network; Latentsemantic analysis; Phonetic features; Spoken language recognition; Support vectormachine; Vector space model

Indexed keywords

ACOUSTIC CHARACTERIZATION; CO-OCCURRENCE STATISTICS; DATA-DRIVEN MODELING; EXPERIMENTAL CONDITIONS; EXPERIMENTAL EVIDENCE; FEATURE VECTORS; FUNDAMENTAL UNITS; LATENTSEMANTIC ANALYSIS; MAXIMAL FIGURE OF MERIT; MODELING APPROACH; PHONETIC FEATURES; SPOKEN LANGUAGES; VECTOR SPACE MODELS;

NEURAL NETWORKS;

VECTOR SPACES;

EID: 84867333761     PISSN: 08852308     EISSN: 10958363     Source Type: Journal    
DOI: 10.1016/j.csl.2012.05.001     Document Type: Article

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