Iflytek Co., Ltd.

University of Science and Technology of China

Qingfeng Liu

Guoping Hu

Si Wei

Yu Hu

Cong Liu

Jun Du

Jia Pan

Jianqing Gao

Shifu Xiong

Tingting He

Qinghua Pan

Bo Zhu

Yintian Zhang

Yulong Hu

Jiajia Wu

Jinshui Hu

Lirong Dai

Jianshu Zhang

A speech recognition method and related products are provided. The method includes acquiring a to-be-recognized speech and a configured hot word library; determining, based on the to-be-recognized speech and the hot word library, an audio-related feature used at a current decoding time instant; determining, based on the audio-related feature, a hot word-related feature used at the current decoding time instant from the hot word library; and determining, based on the audio-related feature and the hot word-related feature, a recognition result of the to-be-recognized speech at the current decoding time instant.

Speech recognition method, apparatus and device, and storage medium

A method for recognizing a character includes: obtaining a character; converting the character into a radical based character recognition result, where the radical based character recognition result comprises symbols indicating radicals of the character and a structure of the radicals of the character; and recognizing the character based on the radical based character recognition result.

Method, apparatus and storage medium for recognizing character

An intelligent scoring method and system for a text objective question, the method comprising: acquiring an answer image of a text objective question (); segmenting the answer image to obtain one or more segmentation results of an answer string to be identified (); determining whether any of the segmentation results has the same number of characters as the standard answer (); if no, the answer is determined to be wrong (); otherwise, calculating identification confidence of the segmentation result having the same number of words as the standard answer, and/or calculating the identification confidence of respective characters in the segmentation result having the same number of words as the standard answer (); determining whether the answer is correct according to the calculated identification confidence (). The method can automatically score text objective questions, thus reducing consumption of human resource, and improving scoring efficiency and accuracy.

Intelligent scoring method and system for text objective question

The present invention relates to a speech recognition method and system based on user personalized information. The method comprises the following steps: receiving a speech signal; decoding the speech signal according to a basic static decoding network to obtain a decoding path on each active node in the basic static decoding network, wherein the basic static decoding network is a decoding network associated with a basic name language model; if a decoding path enters a name node in the basic static decoding network, network extending is carried out on the name node according to an affiliated static decoding network of a user, wherein the affiliated static decoding network is a decoding network associated with a name language model of a particular user; and returning a recognition result after the decoding is completed. The recognition accuracy rate of user personalized information in continuous speech recognition may be raised by using the present invention.

Speech recognition method and system based on user personalized information

A method and system for endpoint automatic detection of audio record is provided. The method comprises the following steps: acquiring a audio record text and affirming the text endpoint acoustic model for the audio record text; starting acquiring the audio record data of each frame in turn from the audio record start frame in the audio record data; affirming the characteristics acoustic model of the decoding optimal path for the acquired current frame of the audio record data; comparing the characteristics acoustic model of the decoding optimal path acquired from the current frame of the audio record data with the endpoint acoustic model to determine if they are the same; if yes, updating a mute duration threshold with a second time threshold, wherein the second time threshold is less than a first time threshold. This method can improve the recognizing efficiency of the audio record endpoint.

Method and system for endpoint automatic detection of audio record

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Anhui, China

Qingfeng Liu