Error Analysis and Improving Speech Recognition for Latvian language
Askars Salimbajevs, Jevgenijs Strigins · Recent Advances in Natural Language Processing · 2015
Developing a large vocabulary automatic speech recognition system is a very difficult task, due to the high variations in domain and acoustic variability. This task is even more difficult for the Latvian language, which is very rich morphologically and in which one word can have dozens of surface forms. Although there is some research on speech recognition for Latvian, Latvian ASR remains behind “big” languages such as English, German etc. In order to improve the performance of Latvian ASR, it is important to understand what errors does it make and why. In this paper, the authors analyze the most common errors of Latvian ASR. Based on this, baseline system WER is improved from 30.94% to 28.43%.