Yusuke Ijima

Learn More
This paper proposes a technique for emotional speech recognition which enables us to extract paralinguistic information as well as linguistic information contained in speech signal. The technique is based on style estimation and style adaptation using multiple-regression HMM. Recognition process consists of two stages. In the first stage, a style vector(More)
To allow the average-voice-based speech synthesis technique to generate synthetic speech that is more similar to that of the target speaker, we propose a model training technique that introduces the label of speaker class. Speaker class represents the voice characteristics of speakers. In the proposed technique , first, all training data are clustered to(More)