Now showing items 21-23 of 23
Evaluation of Mixed Deep Neural Networks for Reverberant Speech Enhancement
Speech signals are degraded in real-life environments, as a product of background noise or other factors. The processing of such signals for voice recognition and voice analysis systems presents important challenges. One ...
Discriminative multi-stream postfilters based on deep learning for enhancing statistical parametric speech synthesis
Statistical parametric speech synthesis based on Hidden Markov Models has been an important technique for the production of artificial voices, due to its ability to produce results with high intelligibility and sophisticated ...
Reconstructing fundamental frequency from noisy speech using initialized autoencoders
In this paper, we present a new approach for fundamental frequency (f0) detection in noisy speech, based on Long Short-term Memory Neural Networks (LSTM). f0 is one of the most important parameters of human speech. Its ...