Jio Haptik bags top honours at leading natural language processing conference
The contribution of Haptik towards NLP research was recognised alongside Google Brain, OpenAI, and IBM Research.
Jio Haptik Technologies Limited — a leading conversational AI company and a subsidiary of Reliance Jio Platforms — on Thursday said it was recently recognised for its exceptional contribution at EMNLP 2020.
Empirical Methods in Natural Language Processing (EMNLP) is a leading conference in Tier-I venue for researchers around the world to publish results that push the boundaries of Natural Language Processing (NLP).
The company introduced three new datasets for the NLP community that has the potential to emerge as a major benchmark for Intent Detection globally. The paper also benchmarks intent detection accuracy of Haptik which is at par and in some cases better than the likes of Google's DialogFlow, Microsft LUIS and Rasa.
The authors of the paper presented HINT3: Raising the bare for intent detection in the wild, alongside other companies like Google Brain, IBM, and Open AI at the Insights Workshop EMNLP 2020.
The publication also drew attention towards existing gaps in the performance of chatbots in the real world. Unlike current datasets that contain crowd-sourced user queries, HINT3 contains samples of real user queries, and the likelihood of this performance translating proportionally to customer experience (CSAT) is very high.
According to Haptik, while analysing the best-case performance of all the platforms on queries, which are in the scope of bots present in training data, it performed exceptionally well.
Even though chatbots and virtual assistants get trained and learn over time as interactions increase, it’s equally important to provide the best customer experience during the initial days of implementation. Upon analysing the performance of leading vendors with even lesser data containing sufficient signal to learn, Haptik stood out.
This means, for companies, where getting sufficient data is a challenge, its solution can be cost-effective and efficient, the startup said.
Haptik CTO Swapan Rajdev said, “I am extremely proud of the hard work, testing, and performance standards that have gone into building our NLU technology. With the HINT-3 dataset, we are trying to give back to our developer community by ensuring better benchmarking standards for everyone.”
Haptik’s conversational AI platform has touched over 100 million devices and processed over three billion conversations to date.
Edited by Suman Singh
