3 accepted papers
With the development of globalization, automatic emotion recognition has faced a new challenge in the multi-culture scenario - to generalize across different cultures. Previous works mainly rely on multi-cultural datasets to address the cross-culture discrepancy, which are expensive to collect. In t…
In this paper, we propose a cross-lingual deep neural network (DNN) based submodular unbiased data selection approach for low-resource keyword search (KWS). A small amount (e.g. one hour) of transcribed data is used to conduct cross-lingual transfer. The frame-level senone sequence activated by the…
In this paper, we propose to use acoustic feature based submodular function optimization to select a subset of untranscribed data for manual transcription, and retrain the initial acoustic model with the additional transcribed data. The acoustic features are obtained from an unsupervised Gaussian mi…