1、2950 英文单词， 1.6 万英文字符 ， 中文 4900 字 文献出处： Errattahi R , Hannani A E , Ouahmane H . Automatic Speech Recognition Errors Detection and Correction: A ReviewJ. Procedia Computer Science, 2018, 128:32-37. Automatic Speech Recognition Errors Detection and Correction: A Review Rahhal Errattahi, Asmaa El Hanna
2、ni, Hassan Ouahmane Abstract Even though Automatic Speech Recognition (ASR) has matured to the point of commercial applications, high error rate in some speech recognition domains remain as one of the main impediment factors to the wide adoption of speech technology, and especially for continuous la
3、rge vocabulary speech recognition applications. The persistent presence of ASR errors have intensified the need to find alternative techniques to automatically detect and correct such errors. The correction of the transcription errors is very crucial not only to improve the speech recognition accura
4、cy, but also to avoid the propagation of the errors to the subsequent language processing modules such as machine translation. In this paper, basic principles of ASR evaluation are first summarized, and then the state of the current ASR errors detection and correction research is reviewed. We focus
5、on emerging techniques using word error rate metric. Keywords: Automatic Speech Recognition; ASR Error Detection; ASR Error Correction; ASR evaluation; 1. Introduction Automatic Speech Recognition (ASR) systems aims at converting a speech signal into a sequence of words either for text-based communi
6、cation purposes or for device controlling. The purpose of evaluating ASR systems is to simulate human judgement of the performance of the systems in order to measure their usefulness and assess the remaining difficulties and especially when comparing systems. The standard metric of ASR evaluation is the Word Error Rate, which is defined as the proportion of word errors to words processed. ASR has matured to the point of commercial applications by providing transcription with an acceptable lev
