Deep Learning based voice conversion
Voice conversion using Deep Learning
- Implemented Bidirectional LSTMs and Encoder-Decoder Recurrent Neural Networks for voice conversion
- Applied Dynamic Time Warping to align mel-cepstral coefficients of source and target speaker
- Improved the conversion fidelity by 12.5\% using Attention mechanism to handle long-range dependencies