Large-Vocabulary Mandarin Speech Recognition using Hierarchical Language Model
碩士 === 國立交通大學 === 電信工程研究所 === 99 === It’s difficult to list all words in recognizer’s vocabulary for large-vocabulary speech recognition, so we present an approach for modeling out of vocabulary (OOV) words. In this thesis, we choose three types of word in Mandarin such as determinative-measure...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2010
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| Online Access: | http://ndltd.ncl.edu.tw/handle/76476966608462857598 |
| Summary: | 碩士 === 國立交通大學 === 電信工程研究所 === 99 === It’s difficult to list all words in recognizer’s vocabulary for large-vocabulary speech recognition, so we present an approach for modeling out of vocabulary (OOV) words. In this thesis, we choose three types of word in Mandarin such as determinative-measure compound word, person name and affixation to deal with this OOV problem. Words are converted to the sub-word units and searched for in the hypotheses to cover more new words through the use of flexible sub-word units.
The main focus of this study is to use the grammar and semantic information to construct a hierarchical language model for these three types of word. The language model will be added to promote the recognition performance and hope to recognize more meaningful long-term units such as word and word-chunk.
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