Automatic Speaker Characterization; Identification of Gender, Age, Language and Accent from Speech Signals (2014)
Abstract / truncated to 115 words
Speech signals carry important information about a speaker such as age, gender, language, accent and emotional/psychological state. Automatic recognition of speaker characteristics has a wide range of commercial, medical and forensic applications such as interactive voice response systems, service customization, natural human-machine interaction, recognizing the type of pathology of speakers, and directing the forensic investigation process. This research aims to develop accurate methods and tools to identify diﬀerent physical characteristics of the speakers. Due to the lack of required databases, among all characteristics of speakers, our experiments cover gender recognition, age estimation, language recognition and accent/dialect identiﬁcation. However, similar approaches and techniques can be applied to identify other characteristics such as emotional/psychological state. For speaker ... toggle 6 keywordsspeech signal – automatic speaker characterization – speaker gender detection – speaker age estimation – language recognition – accent recognition
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