SYSTEM SIMULATING A DECISIONAL PROCESS IN A MAMMAL BRAIN ABOUT MOTIONS OF A VISUALLY OBSERVED BODY

    公开(公告)号:US20220284303A1

    公开(公告)日:2022-09-08

    申请号:US17632718

    申请日:2020-08-03

    IPC分类号: G06N3/10 G06N10/60

    摘要: A system simulating a decisional process in a mammal brain about characteristics of motions related to body gestures of a visually observed body through a simulated visual path is provided. The system includes an interface toward simulated neuronal structures, the interface at least converting luminous information of the observed body to an optic flow data stream conveying information related to the visually observed body and that can be processed in the simulated neuronal structures, the system being a feed-forward system and comprising hierarchically from the visual observation to the decision: the simulated visual path and its interface, a simulated local motion direction detection neuronal structure for the detection of motion directions with receptive fields, a simulated opponent motions detection neuronal structure, a simulated complex patterns detection neuronal structure, and a simulated motion pattern detection neuronal structure.

    Speech recognition method and apparatus

    公开(公告)号:US11282501B2

    公开(公告)日:2022-03-22

    申请号:US16656700

    申请日:2019-10-18

    摘要: A speech recognition method and apparatus, including implementation and/or training, are disclosed. The speech recognition method includes obtaining a speech signal, and performing a recognition of the speech signal, including generating a dialect parameter, for the speech signal, from input dialect data using a parameter generation model, applying the dialect parameter to a trained speech recognition model to generate a dialect speech recognition model, and generating a speech recognition result from the speech signal by implementing, with respect to the speech signal, the dialect speech recognition model. The speech recognition method and apparatus may perform speech recognition and/or training of the speech recognition model and the parameter generation model.