Automatic Turn-Level Language Identification for Code-Switched Spanish–English Dialog
2019; Springer Science+Business Media; Linguagem: Inglês
10.1007/978-981-13-9443-0_5
ISSN1876-1119
AutoresVikram Ramanarayanan, Robert Pugh, Yao Qian, David Suendermann‐Oeft,
Tópico(s)Speech Recognition and Synthesis
ResumoWe examine the efficacy of text and speech-based features for language identification in code-switched human-human dialog interactions at the turn level. Ramanarayanan, Vikram We extract a variety of character- and word-based text features and pass them into multiple learners, including conditional random fields, logistic regressors and deep neural networks. Pugh, Robert We observe that our best-performing text system significantly outperforms a majority vote baseline. Qian, Yao We further leverage the popular i-Vector approach in extracting features from the speech signal and show that this outperforms a traditional spectral feature-based front-end as well as the majority vote baseline. Suendermann-Oeft, David
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