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Determining how a speaker is engaged in a conversation is crucial for achieving harmonious interaction between computers and humans. In this study, a fusion approach was developed based on psychological factors to recognize Interaction Style ( ) in spoken conversation, which plays a key role in creating natural dialogue agents. The proposed Fused Cross-Correlation Model (FCCM) provides a unified...
Bilingual speakers are known for their ability to code-switch or mix their languages during communication. This phenomenon occurs when bilinguals substitute a word or phrase from one language with a phrase or word from another language. For code-switching speech recognition, it is essential to collect a large-scale code-switching speech database for model training. In order to ease the negative effect...
This study presents a novel approach to unsupervised pronunciation grammar growing for non-native speech recognition. Unsupervised pronunciation grammar growing includes pronunciation variation graph construction and non-native grammar generation. Knowledge-based and data-driven approaches are considered for variation graph construction. The measurement of confidence and support is used for grammar...
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