Tencent Technology (shenzhen) Company Limited

Freeman It Limited

Huawei Technologies Co., Limited

Future Wei Technologies, Inc.

Huawei Device Co., Ltd.

Tencent Technology Company Limited

Haibo Liu

Xiang Zhang

Bo Song Chen

Li Hui Lu

Shuai Yue

Eryu Wang

Feng Rao

Lou Li

Jian Hua Liu

Jing Wang

Qiang Wu

Feng Xie

Chen-Xiong Zhang

Lu Li

Duling Lu

Jingsong Xu

Jian Zhang

Meiwen Yang

Jianxiong Ma

Kui Fang

Ying Cui

Wei Chen

Hai Chen

Dadong Xie

Yongfeng Tu

Qiuge Liu

Keqiang Gao

Jinjun He

Linghui Kong

Fengguo Yang

Yibing Wang

Lu Ll

Zefeng Ni

Electric scooter

Vacuum cleaner and air inflator

Electric bicycle

Electric kids motorcycle

A speech emotion detection system may obtain to-be-detected speech data. The system may generate speech frames based on framing processing and the to-be-detected speech data. The system may extract speech features corresponding to the speech frames to form a speech feature matrix corresponding to the to-be-detected speech data. The system may input the speech feature matrix to an emotion state probability detection model. The system may generate, based on the speech feature matrix and the emotion state probability detection model, an emotion state probability matrix corresponding to the to-be-detected speech data. The system may input the emotion state probability matrix and the speech feature matrix to an emotion state transition model. The system may generate an emotion state sequence based on the emotional state probability matrix, the speech feature matrix, and the emotional state transition model. The system may determine an emotion state based on the emotion state sequence.

Speech emotion detection method and apparatus, computer device, and storage medium

Multifunctional off-road scooter

An audio event detection method including performing a framing processing on an audio to obtain audio data for each time period in the audio and extracting a specified feature vector from the audio data of each time period; inputting the specified feature vector of the audio data to a Recurrent Neural Network/Bidirectional Recurrent Neural Network (RNN/BI-RNN) model, to obtain a posterior probability of each pre-set audio event in the audio data of each time period; obtaining, for each time period, a target audio event of the audio data according to the posterior probability of each audio event in the audio data and a pre-set audio decoding algorithm; and extracting an optimal audio data sequence of the target audio event from the audio data of each time period.

Audio event detection method and device, and computer-readable storage medium

A spherical/elliptical single-wheeled vehicle comprises a motor, pedals and a wheel. The motor comprises a motor shell and a spindle having two ends fixedly connected to the pedals respectively. The wheel is spherical or elliptical and is of a hollow structure having two ends formed with openings, and the wheel is arranged on the motor housing in a sleeving manner, is fixedly connected to the motor housing, and comprises a sleeve made from an elastic material. The wheel has a large contact area with the ground at any angles, thus the controllability of the single-wheeled vehicle is greatly improved; in addition, users can get on the vehicle easily, and the operation difficulty of the single-wheeled vehicle is lowered, and user experience is improved; and the reinforcing shells are used to support the two ends of the spherical/elliptical wheel, so that the structural stability of the spherical/elliptical single-wheeled vehicle is improved.

Spherical/elliptical single-wheeled vehicle

A method for establishing a voice activity detection model includes obtaining a training audio file and a target result of the training audio file, framing the training audio file to obtain an audio frame, extracting an audio feature of the audio frame, the audio feature comprising at least two types of features, inputting the extracted audio feature as an input to a deep neural network model, performing information processing on the audio feature through a hidden layer of the deep neural network model, and outputting the processed audio feature through an output layer of the deep neural network model, to obtain a training result; determining a bias between the training result and the target result, and inputting the bias as an input to an error back propagation mechanism, and updating weights of the hidden layer until the deep neural network model reaches a preset condition.

Voice activity detection method, method for establishing voice activity detection model, computer device, and storage medium

Growing community of inventors

Shenzhen, China

Haibo Liu