Methods for Spoken Language Identification
نویسندگان
چکیده
In this paper, we explore several machine learning techniques for classifying spoken language. In particular, we construct algorithms which utilize various spectral features derived from English and Mandarin Chinese phone call audio to predict the language to which the phone call belongs. We investigate multiple feature sets and modeling approaches, and find that Gaussian Mixture Models, combined with shifted delta cepstra (SDC) features, achieve the
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Identifying spoken language automatically is to identify a language from the speech signal. Language identification systems can be divided into two categories, spectral-based methods and phonetic-based methods. In the former, short-time characteristics of speech spectrum are extracted as a multi-dimensional vector. The statistical model of these features is then obtained for each language. The ...
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