Beijing Baidu Netcom Science and Technology Co., Ltd.

Beijing Qihoo Technology Company Limited

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

Beijing Baidu Netcom Science Technology Co., Ltd

Ming Wen

Chao Li

Weixin Zhu

Xin Li

Jianwei Sun

Zhen Wu

Xiaoyin Fu

Qiguang Zang

Jiaxiang Ge

Maoren Zhou

A method for mining feature information, an apparatus for mining feature information and an electronic device are disclosed. The method includes: determining a usage scenario of a target device; obtaining raw audio data including real scenario data, speech synthesis data, recorded audio data and other media data; generating target audio data of the usage scenario by simulating the usage scenario based on the raw audio data; and obtaining feature information of the usage scenario by performing feature extraction on the target audio data.

Method and apparatus for mining feature information, and electronic device

Embodiments of the present disclosure include methods, apparatuses, devices, and computer readable storage mediums for processing far-field environmental noise. The method can comprise processing collected far-field environmental noise to a noise segment in a predetermined format. The method can further comprise establishing a far-field voice recognition model based on the noise segment and a near-field voice segment; and determining validity of the noise segment based on the far-field voice recognition model. The solution of the present disclosure can optimize anti-noise performance of the far-field voice recognition model by differentiated training of noise in different user scenarios of a far-field voice recognition product.

Method, apparatus, device and storage medium for processing far-field environmental noise

A voice recognition method is provided by embodiments of the present application. The method includes: obtaining a voice signal to be recognized; and recognizing a current frame in the voice signal using a pre-trained causal acoustic model, according to the current frame in the voice signal and a frame within a preset time period before the current frame, the causal acoustic model being derived based on a causal convolutional neural network training. In the method provided by the embodiments of the present application, only the information of the current frame and the frame before the current frame is used when performing the recognition of the current frame, thereby solving a problem in voice recognition technologies based on prior art convolutional neural network where a hard delay is created because there is a need to wait for the frames after the current frame, improving the timeliness of the voice recognition.

Voice recognition method, apparatus, device and storage medium

Embodiments of the present disclosure provide a method and a device for generating far-field speech data, a computer device and a computer readable storage medium. The method includes obtaining environmental noise in real environment and adjusting near-field speech data in a near-field speech data set based on the environmental noise, further includes generating far-field speech data based on adjusted near-field speech data and the environmental noise.

Method and device for generating far-field speech data, computer device and computer readable storage medium

Disclosed are a method and an apparatus for determining a phishing website. The method comprises: a server determining whether a target website accessed by a client is a gray website, the gray website being a website neither in a preset blacklist nor in a whitelist; the client acquiring the browsing information of the gray website in the local client, and determining whether the browsing information meets a preset condition; if yes, determining that the gray website is a non-phishing website; if not, the client acquiring the domain name feature information of the gray website, and when the domain name feature information conforms to a pre-configured rule, determining that the gray website is a phishing website.

Method and apparatus for determining phishing website

Disclosed are a method and an apparatus for determining a phishing website. The method comprises: a server determining whether a target website accessed by a client is a gray website, the gray website being a website neither in a preset blacklist nor in a whitelist; the client acquiring the browsing information of the gray website in the local client, and determining whether the browsing information meets a preset condition; if yes, determining that the gray website is a non-phishing website; if not, the client acquiring the domain name feature information of the gray website, and when the domain name feature information conforms to a pre-configured rule, determining that the gray website is a phishing website. Through the present disclosure, when the server cannot determine whether the website accessed by the client is a phishing website, or when the server fails, the latest generated phishing website can be intercepted the first time at the client, and most of the phishing websites can be intercepted, thereby ensuring the network security.

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Beijing, China

Ming Wen