| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2020: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2019: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Outline of Final Research Achievements |
In automatic speech recognition, common models trained with general texts have limited performance for specialized topics, such as those in classroom lectures and academic talks. To deal with this problem, language model adaptation is often conducted. In this study, we investigated automatic adaptation framework of neural-network-based language models by using texts relevant to the topics in the target speech, and incorporate it into our system of automatic captioning, which produces captions for both of recorded audio and real-time audio, with the adapted language models.
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