Baidu Online Network Technology (Beijing) Co., Ltd.

Beijing Baidu Netcom Science Technology Co., Ltd

Beijing Naura Microelectronics Equipment Co., Ltd.

Guibin Wang

Lei Jia

Yu Zhang

Xi Chen

Tao Chen

Tao Sun

Xu Chen

Jing Yang

Gang Wei

Jing Jing Wei

Zhen Wu

Sheng Qian

Jinfeng Bai

Zhijian Wang

Ce Zhang

Wenfu Wang

Hao Dong

Xiaokong Ma

Chenxi Sun

Xingyuan Peng

Huanxin Zheng

Chuanlei Zhai

Shijun Cong

Xin Yue

The present disclosure provides a power adjustment method of an upper electrode power supply of a semiconductor process apparatus. The method includes obtaining a processing load of an upper electrode power supply of a reference process chamber and a processing load of an upper electrode power supply of a current process chamber corresponding to semiconductor process step, when starting to perform a semiconductor process step, determining a power compensation coefficient for the current process chamber relative to the reference process chamber based on the processing load of the current process chamber and the processing load the reference process chamber, and controlling the upper electrode power supply to output compensation power. The compensation power is a product of the set power of the upper electrode power supply of the current process chamber corresponding to the semiconductor process step and the corresponding power compensation coefficient.

Power adjustment method of upper electrode power supply and semiconductor process apparatus

A method for compressing a neural network model includes acquiring a to-be-compressed neural network model. A first bit width, a second bit width and a target thinning rate corresponding to the to-be-compressed neural network model are determined. A target value is obtained according to the first bit width, the second bit width and the target thinning rate. Then the to-be-compressed neural network model is compressed using the target value, the first bit width and the second bit width to obtain a compression result of the to-be-compressed neural network model.

Method and apparatus for compressing neural network model

A data processing method and device are provided. The method includes: performing a forward calculation of a neural network on global data to obtain intermediate data for a reverse calculation of the neural network; storing the intermediate data in a buffer unit; reading the intermediate data from the buffer unit; and performing the reverse calculation of the neural network on the intermediate data to obtain a result of the reverse calculation. According to embodiments, in the reverse calculation of the neural network, the number of accessing the global memory is reduced, thereby reducing the computational time cost and increasing the data processing speed.

Data processing method and device

The present disclosure discloses an interactive voice-control method and apparatus, a device and a medium. The method includes: obtaining a sound signal at a voice interaction device and recognized information that is recognized from the sound signal; determining an interaction confidence of the sound signal based at least on at least one of an acoustic feature representation of the sound signal and a semantic feature representation associated with the recognized information; determining a matching status between the recognized information and the sound signal; and providing the interaction confidence and the matching status for controlling a response of the voice interaction device to the sound signal.

Interactive voice-control method and apparatus, device and medium

The disclosure provides a method, an apparatus, a device, and a computer-readable storage medium for speech synthesis in parallel. The method includes: splitting a piece of text into a plurality of segments; based on the piece of text, obtaining a plurality of initial hidden states of the plurality of segments for a recurrent neural network. The method further includes: synthesizing the plurality of segments in parallel based on the plurality of initial hidden states and input features of the plurality of segments.

Method, device, and computer-readable storage medium for speech synthesis in parallel

Growing community of inventors

Beijing, China

Guibin Wang