1. Add options to enable and disable RNN weights sharing.
2. Set rnn_layer_size to 2048 by default.
3. Revert back the striding steps of 1st conv layer from 2 to 3.
4. Revert back to BRelu.
Above follows DS2 papers.
Summary:
1. Add missing is_local argument (when set False, use pserver).
2. Add exception thrown if cp failed.
3. Add cloud mkdir if not cloud path for uploading does not exist.
4. Fix a bug using common path ./local_manifest for all nodes. (convert to /local_manifest)
5. Refine coding style.
1. Refactor data preprocessor with new added class AudioSegment, SpeechSegment, TextFeaturizer, AudioFeaturizer, SpeechFeaturizer.
2. Add data augmentation interfaces and class AugmentorBase, AugmentationPipeline, VolumnPerturbAugmentor etc..
3. Seperate normalizer's mean and std computing from training, by adding FeatureNormalizer and a seperate tool compute_mean_std.py.
4. Re-organize directory.
2. Fix incorrect batch-norm usage in RNN.
3. Fix overlapping train/dev/test manfests.
4. Update README.md and requirements.txt.
5. Expose more arguments to users in argparser.
6. Update all other details.
Xinghai Sun
Yibing Liu
dangqingqing
yangyaming