A neural network keyword search system for telephone speech

Abstract

In this paper we propose a pure “neural network” (NN) based keyword search system developed in the IARPA Babel program for conversational telephone speech. Using a common keyword search evaluation metric, “actual term weighted value” (ATWV), we demonstrate that our NN-keyword search system can achieve a performance similar to a comparible but more complex and slower “hybrid deep neural network - hidden markov model” (DNN-HMM Hybrid) based speech recognition system without using either an HMM decoder or a language model.