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- W4285102018 abstract "Speech recognition has many application scenarios, such as Interactive Voice Response, and voice commands in games. Many of the voice in these scenarios are short and with high concurrency, so that the performance requirements for speech recognition are very demanding. To boost the performance of speech recognition, one way is to use as much data as possible to train the recognition model to obtain higher accuracy or optimize the structure of the model to make the model smaller and faster. However, doing this is very expensive, it requires us to have very large datasets and a lot of computing resources. To boost the performance of speech recognition without training the model, we have proposed some methods based on our experience, including speech extraction, speech padding, fuzzy pinyin matching, and phonetic similarity matching. Experimental results show that our proposed method indeed boosts the performance of speech recognition. We also discuss the deployment methods we used." @default.
- W4285102018 created "2022-07-14" @default.
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- W4285102018 date "2022-05-27" @default.
- W4285102018 modified "2023-09-26" @default.
- W4285102018 title "Boost Speech Recognition without Training" @default.
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- W4285102018 doi "https://doi.org/10.1109/icaibd55127.2022.9819983" @default.
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