Dynamic Bayesian Networks (DBNs) have been widely studied in multi-modal speech recognition applications. Here, we introduce DBNs into an acoustically-driven talking face synthesi...
Jianxia Xue, Jonas Borgstrom, Jintao Jiang, Lynne ...
In this paper, we propose a novel feature space adaptation technique to improve the robustness of speech recognition in noisy environments. Histogram equalization (HEQ) is an effe...
The last decade has witnessed substantial progress in speech recognition technology, with todays state-of-the-art systems being able to transcribe unrestricted broadcast news audi...
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...