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This is an open source project (formerly named Listen, Attend and Spell - PyTorch Implementation) for end-to-end ASR implemented with Pytorch, the well known deep learning toolkit.

end2endasr

implement end-to-end asr algorithm with tensorflow

flatbuffers

FlatBuffers: Memory Efficient Serialization Library

grid-lstm

Grid Long Short-Term Memory (LSTM) Network

grid-lstm-tensorflow

Examples of using GridLSTM (and GridRNN in general) in tensorflow

kaldi

This is the official location of the Kaldi project.

Tensorflow implementation of "Listen, Attend and Spell" authored by William Chan. This project utilizes input pipeline and estimator API of Tensorflow, which makes the training and evaluation truly end-to-end.

listen-attend-spell

A PyTorch implementation of Listen, Attend and Spell (LAS), an End-to-End ASR framework.

listen-attend-spell-1

PyTorch implementation of Listen Attend and Spell Automatic Speech Recognition (ASR).

listen-attend-spell-v2

PyTorch implementation of Listen Attend and Spell Automatic Speech Recognition (ASR).

lstm-char-cnn

LSTM language model with CNN over characters

lstm-char-cnn-tensorflow

in progress

lstm-human-activity-recognition

Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN (Deep Learning algo). Classifying the type of movement amongst six activity categories - Guillaume Chevalier

lstm_ctc

LSTM CTC End2End Speech Recognition.

models

Models and examples built with TensorFlow

multiplicative-lstm

Use tensorflow to implement multiplicative lstm, and try this on text generation.

multiplicative-lstm-tensorflow

An implementation of multiplicative LSTM in TensorFlow

nabu

Code for end-to-end ASR with neural networks, build with TensorFlow

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