Speech to Text using Azure Cognitive Services (Speech API)

This implementation is for learning purposes. The class speech.py could be used to obtain the transcription from an audio file. This code was adapted from How to use the Speech Services Batch Transcription API from Python.

Could be used in scenarios like call center sentiment analysis, fraud detection, and much more.

Use your creativity to expand the use to have fun to fix a lot of real world problems and feel free to clone this repo and adapt this code for your requirements :)

Activate environment

pipenv shell

Flake8 config

Use the bellow code to adjust the max line length limit flake8 --max-line-length=140

If you use VSCode you can add this config to settings.json adding the code:

"python.linting.flake8Args": [
        "--max-line-length=140",
    ]

Prerequisites

sudo apt-get update
sudo apt-get install libssl1.0.0 libasound2

You also need to follow the requirement from How to use the Speech Services Batch Transcription API from Python to be able to use the API.

Set environment variables

You can find API Key in Quick start section of your API on Azure Portal

export SPEECH_KEY=<KEY_1>

You can find API endpoint in Quick start section of your API on Azure Portal

export REGION=<REGION>

How to run

Run run.py and change the variable BLOB_URI_INPUT with the URL SAS generated in your Storage Account

name: Just a name for the transcript execution

description: Just a description

locale: Is the code of the language that the API need to use during the transcription process. To get the language's code go to this url

properties: Is a dict with the configurations options

output_file: Is the filename with json content

Clean up resources

To clean up resources you can delete the Resource Group or the API using Azure Portal.