ROAR - An NLP/Speech Processing Toolkit for Indic Languages ( Axed and will not be maintained)

Introduction

ROAR is a toolkit for Indic languages that provides a unified interface for various NLP and Speech Processing tasks. It is built on top of PyTorch (WIP). It is based on a lean fork of Nvidia's NeMo toolkit. Majorly targeting Text-to-Speech Synthesis ROAR aims to streamline developer workflow from implementing new models with pre-implemented modularized functions that can be re-used across projects/models.

Instructions

To setup the toolkit, clone the repository and follow the instructions given below.

conda create -n roar python=3.10
pip install Cython
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
pip install -r requirements.txt

TinyLLaMa specific

conda install xformers -c xformers
git clone https://github.com/Dao-AILab/flash-attention
cd flash-attention
python setup.py install
cd csrc/rotary && pip install .
cd ../layer_norm && pip install .
cd ../xentropy && pip install .
cd ../.. && rm -rf flash-attention

After installing the requirements,

Step 1:

python scripts/dataset_processing/tts/extract_sup_data.py \
    manifest_filepath=<manifest_filepath> \
    sup_data_path=<sup_data_path> \
    dataset.sample_rate=<sample_rate> \
    dataset.n_fft=<n_fft> \
    dataset.win_length=<win_length> \
    dataset.hop_length=<hop_length> \

Step 2:

python examples/tts/fastpitch.py \
    --config-name=fastpitch_22050_align \
    train_dataset=<train_dataset_path> \
    validation_datasets=<validation_dataset_path> \
    sup_data_types="['align_prior_matrix', 'pitch', 'speaker_id']" \
    sup_data_path=<sup_data_path> \
    pitch_mean=<pitch_mean> \
    pitch_std=<pitch_std> \
    +exp_manager.create_wandb_logger=True \
    +exp_manager.wandb_logger_kwargs.name="tutorial-FastPitch-multispeaker" \
    +exp_manager.wandb_logger_kwargs.project="NeMo" \

A more in-depth tutorial will be added soon.

ToDo:

• Core NeMo Fork
• NeMo Utils Fork
• Vanilla MHA
• Flash Attention
• TransformerLayer
• One TTS Alignment
• Fastpitch
• HiFi-GAN
• JETS
• ConformerLayer
• Rotary Position Embeddings
• TinyLLaMa

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Disclaimer: All the code in this repository, forked from NeMo, follows the licensing of the original NeMo repository. The code is provided as-is for research purposes only and without any guarantees. Please contact the original authors for any commercial use.