Combination of error detection techniques in automatic speech transcription

Abstract

Speech recognition technology has been around for several decades now, and a considerable amount of applications have been developed around this technology. However, the current state of the art of speech recognition systems still generate errors in the recognizer's output. Techniques to automatically detect and even correct speech transcription errors have emerged. Due to the complexity of the problem, these error detection approaches have failed to ensure both a high recall and a precision ratio. The goal of this paper is to present an approach that combines several error detection techniques to ensure a better classification rate. Experimental results have proven that such an approach can indeed improve on the current state of the art of automatic error detection in speech transcription. © 2011 Springer-Verlag.