Automatic Speech Recognition-based Information Center for Indonesian Language
نویسنده
چکیده
This paper discusses an implementation of CMU Sphinx-4 in an automatic speech recognition-based information center (ASRIC) for Indonesian language. The ASRIC uses a vector space model (VSM) to improve the performance of statistical language model and to recognize the user utterance more flexibly. Testing to an Indonesian speaker shows that VSM is capable of reducing the query error rate in acceptable response time. The VSM also make ASRIC more flexible to recognize user’s spoken sentences which misses some keywords, contains random ordered words, or consists of unimportant words.
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تاریخ انتشار 2013