<jupyter_start><jupyter_text>INSTALLING DEPENDENCIES<jupyter_code>## Install dependencies
!pip install wget
!apt-get install libsndfile1 ffmpeg
!pip install unidecode
!pip install matplotlib>=3.3.2
!pip install torchaudio
## Install NeMo
!python -m pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[all]


## Grab the config we'll use in this example
!mkdir configs
!wget -P configs/ https://raw.githubusercontent.com/NVIDIA/NeMo/main/examples/asr/conf/config.yaml

!python -m pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[all]
pip install imgaug==0.2.5
pip install Sphinx==2.0.0
pip install folium==0.2.1
pip install Sphinx==2.0.0
pip install urllib3==1.25.4
## Install dependencies
!pip install wget
!apt-get install libsndfile1 ffmpeg
!pip install unidecode
!pip install matplotlib>=3.3.2
!pip install torchaudio
## Install NeMo
!python -m pip install git+https://github.com/NVIDIA/NeMo.git@main#egg=nemo_toolkit[all]

## Grab the config we'll use in this example
!mkdir configs
!wget -P configs/ https://raw.githubusercontent.com/NVIDIA/NeMo/main/examples/asr/conf/config.yaml
!pip install ffmpeg-python<jupyter_output>Collecting ffmpeg-python
  Downloading https://files.pythonhosted.org/packages/d7/0c/56be52741f75bad4dc6555991fabd2e07b432d333da82c11ad701123888a/ffmpeg_python-0.2.0-py3-none-any.whl
Requirement already satisfied: future in /usr/local/lib/python3.6/dist-packages (from ffmpeg-python) (0.18.2)
Installing collected packages: ffmpeg-python
Successfully installed ffmpeg-python-0.2.0<jupyter_text>IMPORTING NECESSARY FILES<jupyter_code>import os
from omegaconf import OmegaConf<jupyter_output><empty_output><jupyter_text>Preprocessing Datas<jupyter_code>tmp = 'src'
data_folder = 'data'
if not os.path.exists(tmp):
  os.makedirs(tmp)
if not os.path.exists(data_folder):
  os.makedirs(data_folder)
script = os.path.join(tmp, 'process_vad_data.py')
if not os.path.exists(script):
    !wget -P $tmp https://raw.githubusercontent.com/NVIDIA/NeMo/$BRANCH/scripts/process_vad_data.py
speech_data_root = os.path.join(data_folder, 'google_dataset_v2')
background_data_root = os.path.join(data_folder, 'google_dataset_v2/google_speech_recognition_v2/_background_noise_')# your <resampled freesound data directory>
out_dir = os.path.join(data_folder, 'manifest')
if not os.path.exists(speech_data_root):
    os.mkdir(speech_data_root)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.1174055829228243, 'fraction_numerical': 0.03366174055829228, 'mean_word_length': 6.146627565982405, 'pattern_counts': {'":': 0, '<': 13, '<?xml version=': 0, '>': 15, 'https://': 7, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '264755', 'license': 'Apache-2.0', 'n_tokens_mistral': 968, 'n_tokens_neox': 918, 'n_words': 169, 'path': 'VoiceActivitywithNeMo.ipynb', 'repo_name': 'andreschen33/Yumera', 'size': '2436'}