1. A computer implemented method of an interactive voice response (IVR) system for responding to natural language queries to identify customer intent during a customer interaction, comprising: identifying, by a processor, the customer intent based on key features in a natural language used by a customer during said customer interaction, along with past interactions of said customer with the IVR system, customer relations management (CRM) system attributes, and customer segment attributes, said identifying including: converting speech in a customer's response during the customer interaction into text, wherein the customer response is in the natural language; determining a predicted identity of the customer based on a gender of the customer and an age group of the customer, said determining including identifying the gender based on an analysis of a tone and/or frequency of speech in the customer response and identifying the age group based on an analysis of a type of language and vocabulary used in the customer response; accessing a customer relations management (CRM) system to obtain the CRM attributes associated with the customer and the customer segment attributes, wherein the CRM attributes include past interactions of the customer with the IVR system, wherein the customer segment attributes include attributes associated with the gender and the age group identified based on the customer response; extracting at least one key feature from the text, wherein the at least one key feature is an identified keyword based on a statistical model; computing a probability score of at least one intent associated with the at least one key feature, wherein the probability score of the at least one intent is computed based on the past interactions of the customer and the customer segment attributes, the past interactions including an intent sequence of previous customer interactions.