Case Study

Crowdsourcing solutions for a real-world business problem

About Exotel

Exotel aspires to be the one-stop solution for voice-based communication for businesses, which typically have thousands of customer interactions every day. In India, most of this happens on the phone.

An interesting challenge that Exotel faced was offering businesses useful information and intelligence based on their conversations. Exotel wanted to see how some of the smartest engineering minds would approach this problem.

Goal

Detection of emotions from audio is an unsolved problem. The goal was to create a system that detects emotions from audio and flags conversations based on sentiments, such as happiness, sadness, anger, etc.

What’s Exotel's story?

Exotel was founded in 2011 by three techies. Today, it has nearly 100 employees and a strong presence in Southeast Asia. Exotel offers a cloud-based telephony platform that helps businesses communicate with their customers efficiently over calls and via SMS. With over 1300 customers, Exotel powers more than 3 million customer conversations every day and has processed 1.2 billion calls in the past 5 years.

One-of-a-kind Machine Learning hackathon

Theme

Speech recognition

Challenge

Decipher the sentiment from a huge data set of voice samples

Duration

18 days

The participants were given sample audio files (training data set) and asked to use speech-recognition algorithms and machine learning to write code that would use the voice in the audio files as input and recognize the emotion behind it. The code would then be run across thousands of voice samples to choose the best model.

What was the outcome?

4548 Registrations

218 Teams

18 Days

1 Winner

Innovate and build a better business