HUMAN SPEECH RECOGNITION FOR RECOMMENDATION IN CONVERSATIONS USING KEYWORD EXTRACTION AND CLUSERING

Abstract

speech Recognition is the process of automatically recognizing a word spoken by a specific speaker based
on that information which are included in speech waves. Now days there are rapid growth of wireless
communications, hence the need for voice recognition techniques has been increased greatly.
In this Paper we are going to describe the problem of keyword extraction from conversations, with this paper user
can access the keywords which are document relevant for each short conversation fragment, which can be
recommended to users. Sometimes, even a short fragment includes different types of words, which are potentially
related to different topics. However, errors can be introducing into system or conversation by using automatic speech
recognition system. To extract keyword from the output of ASR technique we use one algorithm. It is based on the sub
modular functions which gives range of different words and reduces the noise. Then use a method to obtain a multiple
topic from this keyword set only for to access the one relevant recommended document.