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A serverless infrastructure to perform sentiment analysis out of audio files.

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🤖 NLPipe

Serverless Sentiment Analysis

By Davide Quaranta, Daniele Solombrino, Edoardo Gabrielli

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What is it?

NLPipe is a serverless infrastructure to perform sentiment analysis out of audio files. It has been developed as a project for the Cloud Computing 2020-2021 course at Sapienza University of Rome.

The system is composed of multiple independent components the perform specific tasks; specifically:

  • A web interface that allows the user to upload audio files.

  • A REST API that handles the interaction between the web interface and the backend.

  • A storage space for the uploaded files.

  • A pipeline of functions, one for each step:

    • Speech to text.
    • Text sentiment analysis.
    • Logic to store final results.
  • A database to store the result of the performed sentiment analysis.

The system is cloud-native for Amazon Web Services and is deployed with the following AWS services:

  • Web interface and API: container on AWS Fargate.
  • Pipeline: chain of functions on AWS Lambda, connected via AWS Destinations.
  • Database: Amazon DynamoDB.
  • Storage: Amazon S3.

How does it work?

The system's architecture, focusing on the AWS services used is the following.

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The interaction flow between the components can be synthesized in the following sequence diagram.

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A serverless infrastructure to perform sentiment analysis out of audio files.

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