openseq2seq
NVIDIA/OpenSeq2Seq
OpenSeq2Seq main goal is to allow researchers to most effectively explore various sequence-to-sequence models. The efficiency is achieved by fully supporting distributed and mixed-precision training. OpenSeq2Seq is built using TensorFlow and provides all the necessary building blocks for training encoder-decoder models for neural machine translation, automatic speech recognition, speech synthesis, and language modeling. Speech-to-text workflow uses some parts of Mozilla DeepSpeech project. Beam search decoder with language model re-scoring implementation (in decoders) is based on Baidu DeepSpeech.