Chengdu Wang'an Technology Development Co., Ltd.

Chengdu Yunke Pharmaceutical Co., Ltd.

Xue Jiang

Tianxiang Wang

Han Wang

Yongqiang Zhu

Mingqi Li

Qimin Deng

Zuoyong Cheng

Maoliang Li

Yonglong Zeng

Yuchun Duan

Sanping Zhu

Dezhong Wen

Disclosed of the present application is relation to deep learning based voice data processing. The voice data to be detected is converted into target text data based on a voice recognition model so that the keyword text corresponding to the predetermined target voice keyword can be converted. Then, the data is matched with the target text data to determine whether the voice data to be detected includes the target voice keyword based on the matching result. Thus, because the voice recognition model is obtained by deep learning based on the obtained voice recognition data training set, it can obtain high-precision target text data, thereby improving the accuracy of subsequent matching. The problem of low accuracy of detecting voice data for keyword detection can therefor be solved.

Voice data processing based on deep learning

The present disclosure relates to a new diphosphonate compound, and the method to prepare the above new diphosphonate compound. The new diphosphonate compound exhibits an activity in inhibiting osteoclast equivalent to alendronate sodium, and a higher activity in affecting the proliferation of osteoplast than the positive control compounds, but the positive control exhibits a weaker effect on osteoblast proliferation. In experimental examples, an administration schedule for the diphosphonate compound is provided.

Diphosphonate compound and a method for preparing the same and an application of the same

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Chengdu, China

Xue Jiang