End-to-End Natural Language Understanding Pipeline for Bangla Conversational Agents

In the history of conversational AI agents, ELIZA [2], [3], one In this era of artificial intelligence (AI), chatbots are becoming of the first rule-based chatbots, took it upon itself to pass the more and more popular every day for their versatility, easy famous Turing Test and pioneer the path of guided computer accessibility, personalizing features, and, more importantly, responses. Even though it failed to pass the test completely, it their ability to generate automated responses. Specifically for surely did not come short in paving the way for other artificial these purposes, we now see an uprise of chatbots everywhere - chatbots, which ranged from responding emotionally (PARRY) from personal to organizational, to business websites or other [2]-[4] to simply having fun conversations by running pattern online platforms, for which it can be trained on suitable data matching (Jabberwacky) [2]. Later, this field got more to make it, in a broader sense, a virtual assistant representative matured with the inception of AI-powered chatbots, namely of the said entities. Dr. Sbaitso [3] and A.L.I.C.E (Artificial Linguistic Internet In the light of this newly emerging scope, we explore the Computer Entity) [2], [4]- which was able to mimic humans possibilities of how these conversational AI agents can be when chatting online or answering questions. From there, integrated properly and thus be an immensely useful tool to it was not long before Smarterchild, Siri, Google Assistant, maintain business activities. To better understand the concurrent and other personalized assistant-like chatbots or conversational chatbots and find possible modifications in them and AI agents came into existence. With conversational AI, now, for further and more customized improvements, we choose a anyone can build, integrate, and use message-based or speechbased trendy chatbot platform Rasa as our study subject.