Jianrong Wu

Shibing Zhang

ZhiHua Bao

Lili Guo

Ming Li

The present application relates to a lexicon learning-based heliumspeech unscrambling method in saturation diving. In a system including divers, a correction network, and an unscrambling network, a common working language lexicon for saturation diving operation is established and is read by the divers respectively in different environments, to generate supervision signals and vector signals of the correction network, and the correction network learns heliumspeeches of the different divers at different diving depths to obtain a correction network parameter, and corrects a heliumspeech of a diver to obtain a corrected speech; and the unscrambling network learns the corrected speech and completes unscrambling of the heliumspeech.

Lexicon learning-based heliumspeech unscrambling method in saturation diving

The present application discloses a method and a system for saturation diving heliumspeech unscrambling based on multi-objective optimization. In a system including a diver and a filter at least, a working language phonetic symbol library and a common working word library for divers are constructed. The divers read them one by one, and a phonetic symbol standard speech library, a phonetic symbol heliumspeech library and a common working word speech library are generated. The filter uses the multi-objective optimization algorithm to design its impulse response coefficients, corrects and unscrambles the tagged and sampled heliumspeech signal word by word, and continuously updates the impulse response coefficients to complete the perfect heliumspeech unscrambling.

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Nantong, China

Jianrong Wu