Case Study
“We did not expect the kind of response that we received both in terms of participation and relevance of submissions. We were quite blown away by some of the ideas. Your platform helped us reach a wide range of programmers and thank you for making it a roaring success. We are planning to make this an annual event.“
Siddharth Ramesh, CTO, 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.
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.
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.
Speech recognition
Decipher the sentiment from a huge data set of voice samples
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.