4 accepted papers
Social media is rocking the world in recent year, which makes modeling social media contents important. However, the heterogeneity of social media data is the main constraint. This paper focuses on inferring emotions from large-scale social media data. Tweets on social media platform, always contain…
Bidirectional long short-term memory (BLSTM) recurrent neural network (RNN) has achieved state-of-the-art performance in many sequence processing problems given its capability in capturing contextual information. However, for languages with limited amount of training data, it is still difficult to o…
Speech is bimodal in nature. There are close correlations between the acoustic speech signals and the visual gestures such as lip movements, facial expressions and head motions. For speech driven talking avatar, how to derive more representative acoustic features from which to predict more accurate…
This paper investigates the incorporation of hidden Markov model (HMM) based emphatic speech synthesis for audio exaggeration into an audio-visual speech synthesis framework for the corrective feedback in computer-aided pronunciation training (CAPT). To improve the voice quality of the synthetic emp…