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pretrained SpeechBrain wav2vec seq2seq+CTC model trained on TIMIT dataset. Created by Kip McCharen, Siddharth Surapaneni, and Pavan Bondalapati

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sys6016_DL_project

Originally from https://github.com/speechbrain/speechbrain/tree/develop/recipes/TIMIT/ASR/seq2seq

TIMIT ASR with seq2seq models.

This folder contains the scripts to train a seq2seq RNNN-based system using TIMIT. TIMIT is a speech dataset available from LDC: https://catalog.ldc.upenn.edu/LDC93S1

How to run

python train.py train/train.yaml

Results

Release hyperparams file Val. PER Test PER Model link GPUs
21-04-08 train_with_wav2vec2.yaml 7.11 8.04 https://drive.google.com/drive/folders/1-IbO7hldwrRh4rwz9xAYzKeeMe57YIiq?usp=sharing 1xV100 32GB

Bash Commands to run in Google Colab

!pip install speechbrain !pip install transformers !git clone https://github.com/kipmccharen/sys6016_DL_project

%cd .. !gdown --id '1EIfBmwiT0RF3-U81-Qu5K4J27N31BdB5' ## --output /content/speechbrain_s2s_wav2vec_ckpt.zip !unzip speechbrain_s2s_wav2vec_ckpt.zip !rm speechbrain_s2s_wav2vec_ckpt.zip

%cd /content/data/trainwav2vec/save/ !gdown --id '1oZunuiwhMLfwtMeKAYJwr4DMjvE1LUIN' --output label_encoder.txt

%cd /content/

!python sys6016_DL_project/train_with_wav2vec2.py sys6016_DL_project/hparams/train_with_wav2vec2.yaml --data_folder /content/data/ --output_folder /content/data/trainwav2vec/ --new_json /content/sys6016_DL_project/data/new_train.json

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pretrained SpeechBrain wav2vec seq2seq+CTC model trained on TIMIT dataset. Created by Kip McCharen, Siddharth Surapaneni, and Pavan Bondalapati

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