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BrazSpeechData Pipeline Script

Introduction

This script is designed to run data pipelines for diarization, transcription, and metadata extraction, specifically for feeding the BrazSpeechData platform. It includes functionalities for exporting corpus datasets and transcribing audio files.

Installation

The script uses Poetry for dependencies management, and keep in mind that the Dockerized version ISN'T working. In order to start using this project, follow the steps bellow:

1. Clone and create venv

First, clone the repo to your desired folder.

git clone https://github.com/nilc-nlp/braz-speech-pipeline.git

Then create a virtual environment to hold the dependencies, with

cd braz-speech-pipeline
python -m venv .venv
source .venv/bin/activate

2. Install your dependencies

Attention! This project needs Python 3.8 or higher to work.

Install the required dependencies by running:

poetry install

If you need to add new dependencies, run:

poetry add <dependency>

3. Google Drive Token

In order to use the Google Drive API, you need to create a token file, similar to the one in example.token.json. To do so, follow the steps on this link and save the file as token.json in the root folder of this project.

This step is necessary to access the raw files on Google Drive. If you don't need to access the raw files, you can skip this step.

Usage

To use this script, navigate to the directory where the script is located and run:

poetry run python main.py [COMMAND] [OPTIONS]

Replace [COMMAND] with one of the commands listed below, and choose between the available options.

If you need any help, run:

poetry run python main.py --help

or

poetry run python main.py [COMMAND] --help

Command Guide

Export Command

Options

Use this command to export corpus datasets in various formats.

Option Description Type Default Required
--corpus_id Corpus ID int None Yes
--output-folder Output folder Path './data/export' No
--export-audio-to-formats List of audio formats to export (e.g., wav, mp3) List[AudioFormat] ["wav", "mp3"] No
--sample-rate Sample rate for audio export int 48000 No
--google-drive-folder-ids List of Google Drive folder IDs for source audios List[str] None No
--filter-format Specify which files format to read from Google Drive AudioFormat None No
--original-audios Whether to export original audios bool False No
--csv Export data to CSV format bool False No
--continuous-text Export concatenated text from audio segments bool False No
--speakers-text Export text files organized by speaker bool False No
--json-metadata Export audio metadata in JSON format bool False No
--textgrid Export data in TextGrid format for use with Praat bool False No
--all Export all data bool False No
--debug When activated, will export only 10 audios bool False No

Running the command

To run the export script, you should use the base command

poetry run python main.py export [OPTIONS]

Then you can specify which data to export by using the options listed above. For example, to export all data from MUPE (corpus 1), run:

poetry run python main.py export --corpus_id 1 --all --google-drive-folder-ids ID_OF_FOLDER_ON_DRIVE --export-audio-to-formats mp3 --debug

If you want everything, but the original audios, you can run:

poetry run python main.py export --corpus_id 1 --csv --textgrid --continuous-text --speakers-text --json-metadata --debug

If you need any help, run:

poetry run python main.py export --help

Export types

CSV

This command will create an export of the entire database in CSV format. It will export on file corpus_{corpus_id}_audios.csv and another one corpus_{corpus_id}_segments.csv. The first, contains a list of all audios inside the corpus, with their metadata. The second, contains a list of all segments for each audio, with their metadata, the ASR transcription and the final transcription. For this last one, it's also exported a .parquet file for faster loading.

Continuous Text

This command will create a text file for each audio, containing the concatenated text of all segments. The text files will be saved in a folder named {audio_name}_concatenated_text.txt inside the output folder.

Speakers Text

This command will create a text file for each audio, containing the text of each segment, organized by speaker. The text files will be saved in a folder named {audio_name}_by_speaker.txt inside the output folder.

JSON Metadata

This command will create a JSON file for each audio, containing the metadata of the audio. The JSON files will be saved in a folder named {audio_name}_metadata.json inside the output folder.

TextGrid

This command will create a TextGrid file for each audio, containing the metadata of the audio. The TextGrid files will be saved in a folder named {audio_name}.textgrid inside the output folder.

Original Audios

This command will create a copy of the original audios, in the format specified by the export-audio-to-formats option. The audios will be saved in a folder named original_audios inside the output folder. You can also specify the final sample-rate for the audios.

Transcribe Command

This script provides functionalities for transcribing audio files using the WhisperX library. It supports various features like diarization, speaker identification, and alignment of transcribed segments with audio, specifically tailored for processing audio datasets.

Options

Use this command to transcribe audio files from specified Google Drive folders.

Option Description Type Required Default
--corpus-id Unique identifier for the corpus int Yes None
--folder-ids List of Google Drive folder IDs containing audio files List[str] Yes None
--output_folder Directory path for saving the output Path No "./data/"
--storage-output-folder-id Instance of Database for database operations Google Drive folder ID to save the transcriptions. If none is provided, the transcriptions will be saved in the same folder as the audios. No None
--format-filter Filter audios by format [wav,mp4,mp3] No None
--save-to-drive Flag to save transcriptions to Google Drive bool No False
--save-to-db Flag to save transcriptions to database bool No False
--transfer-to-server Flag to transfer transcriptions to server bool No False

Running the command

To run the transcribe script, you should use the base command

poetry run python main.py transcribe --corpus_id [CORPU_ID] --folder_ids [IDs] [OPTIONS]

You can choose between the flags: --save-to-drive, --save-to-db and --transfer-to-server. The first one will upload the segments and transcription files back to GoogleDrive, the second will insert the entries on the BrazSpeechPlatform database, and the third will transfer the files to the server, to make them available on the platform.

If you need any help, run:

poetry run python main.py transcribe --help

Future improvements

  • feat add support for other ASR services
  • feat add support for other Repositories other than Google Drive
  • fix Dockerfile for running the script
  • refact inject dependencies on the script for better modularity
  • tests add unit tests for the script