-
公开(公告)号:US20250123812A1
公开(公告)日:2025-04-17
申请号:US18988135
申请日:2024-12-19
Inventor: Yuehao Zhao , Wenjie Li , Chuqing Wang , Yunpeng Peng , Sai Gao , Hui Li , Junwei Xing , Wanpeng Niu , Bingfei Zhang
Abstract: The disclosure provides a code completion method based on a big model. The method includes: determining a first code element where a position to be completed is located in a first code file to be completed; determining a second code file having a dependency relationship with the first code file from a development project to which the first code file belongs; determining, according to the first code element, a second code element whose correlation with the first code element meets a preset condition, in which the second code element belongs to at least one of the first code file or the second code file; and generating a target code corresponding to the position to be completed through a big model based on a signature of the second code element.
-
公开(公告)号:US20230206943A1
公开(公告)日:2023-06-29
申请号:US17891596
申请日:2022-08-19
Inventor: Wenjie Li , Zhanjie Gao , Lei Jia
Abstract: An audio recognizing method, including: performing acoustic feature prediction on the audio to be recognized to obtain first audio prediction result and an acoustic feature reference quantity for predicting an audio recognition result; obtaining second audio prediction result based on the acoustic feature reference quantity; and determining the audio recognition result of the audio to be recognized based on the first audio prediction result and the second audio prediction result, the audio recognition result including unvoiced sound or voiced sound. When determining that the audio is unvoiced sound or voiced sound, the first audio prediction result obtained by performing acoustic feature prediction on the audio to be recognized is used, and the second audio prediction result is obtained in combination with other acoustic feature reference quantities, thereby making the determination result of unvoiced sound or voiced sound of the audio more accurate, to improve the audio quality in speech processing.
-