0. Ensure you have Python 3
1. Clone this repo and cd into it.
2. Go into each folder for specific services and check the README files

• Google Speech-To-Text
• AWS Transcribe
• Microsoft Cognitive Service
• Rev.ai (Temi Speech) API

Please feel free to contribute for other online speech transcriptions that you are aware of.

Ensure you have a folder of audio files in WAV format. (For example, wav_folder)

Example:

wav_folder
├───000561a49624c7c56625e6d8ccd230b15d3f129083b84c19846a9593.wav
├───0005680e7ac8826cff24f15022b67a2651acd691bf897bf3d3e44345.wav
├───000568340cb01e73daaa263d90765a5c213160a75201d642d899b4df.wav
├───00057062512f8dbc62d1691b97d0e6d997f350f41c908956fec02dbd.wav
├───00057091dd6ea751089e57358095034164067c180c4d1730254924ac.wav
├───000574e671847cbc40ef7fa325f39bfb6338a7f7781e09e773702b41.wav
...

Each script will dump the transcriptions in the specified output folder in the following format:

Example:

output_txt_folder
├───000561a49624c7c56625e6d8ccd230b15d3f129083b84c19846a9593.txt
├───0005680e7ac8826cff24f15022b67a2651acd691bf897bf3d3e44345.txt
├───000568340cb01e73daaa263d90765a5c213160a75201d642d899b4df.txt
├───00057062512f8dbc62d1691b97d0e6d997f350f41c908956fec02dbd.txt
├───00057091dd6ea751089e57358095034164067c180c4d1730254924ac.txt
├───000574e671847cbc40ef7fa325f39bfb6338a7f7781e09e773702b41.txt
...

If you have ground truth in the same format as the output folder described above, you can calculate the Word Error Rate (WER) as follows:

0. Prerequisite: pip install jiwer==2.2.0
1. Set the ground truth and prediction folders in the last line of calc_wer.py
2. Run python calc_wer.py

If say suppose you want to compare the online transcription output to the output of your deep learning models, it's easy!

We follow the format of LibriSpeech dataset in this repo.
So ensure you dump the output in that format (same as this repo format) and use the calc_wer.py script to compare the quality.

For example purposes, we have supported the following DL models:

• ESPnet

Please feel free to contribute for other DL models that you are aware of.

Any pull requests or issues for bugs or fixes or new features are warmly welcomed. :-)

You can also check the following Python Libraries for more services:

• SpeechRecognition