Method for translating Szechwan accent and German with RBH (Random Black Hole) neural network model
A neural network model and neural network technology, applied in the application field of the RBH neural network model in artificial intelligence, can solve the problems of high labor intensity for simultaneous interpreters, unacceptable carrying of interpreters, and non-standard Mandarin pronunciation.
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[0013] Example 1: In a long international conference that took up to 5 hours, the speaker spoke fast, and the Chinese speaker spoke with a Sichuan accent, and the Chinese simultaneous interpreters sent by the German side had limited understanding of the Sichuan accent , and after a long period of simultaneous interpretation with a high concentration of attention, the accuracy of the translation gradually decreased with fatigue. Tired, always able to maintain a stable high level of translation accuracy, better than human translators.
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