文章基本信息

标题：Recurrent Neural Network based Language Modeling for Punjabi ASR
其他标题：English
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作者：Vaibhav Kumar
期刊名称：International Journal of Computer Science and Engineering
印刷版ISSN：2278-9960
电子版ISSN：2278-9979
出版年度：2020
卷号：7
期号：9
页码：7-13
DOI：10.14445/23488387/IJCSE-V7I9P102
出版社：IASET Journals
摘要：Deep Learning approaches have been widely known to perform better than statistical approaches. This is the first effort to investigate Recurrent Neural Network-based modeling for Punjabi speech corpus. We propose the Lattice Rescoring based RNNLM approach using the Kaldi toolkit. Experiments on single sentences showed that the Neural networkbased approach performs better than n-gram based modeling approaches. A performance improvement of 7- 9% on word error rate (WER) was observed on top of the state-of-the-art Punjabi speech recognition system.
关键词：automatic speech recognition; recurrent neural network language modeling; lattice rescoring; Punjabi ASR