Method and system for realizing voice age and/or gender recognition service, and medium

A gender recognition and speech recognition technology, applied in speech recognition, speech analysis, instruments, etc., can solve the problems of difficult deployment, poor scalability, and difficult to modify.
CN113192510APending Publication Date: 2021-07-30GUANGZHOU YUNCONG INFORMATION TECH CO LTD
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
GUANGZHOU YUNCONG INFORMATION TECH CO LTD
Publication Date
2021-07-30

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Abstract

The invention relates to the field of voice recognition and particularly relates to a method, a system and a device for realizing voice age and / or gender recognition service and a medium, and aims to solve technical problems of remote accurate calling and simple and convenient deployment of an existing voice age and / or gender recognition model. Therefore, a terminal calls a server through a serialized voice age / gender identification request under a predefined GRPC framework, and the server identifies the age / gender through a set age / gender voice identification service; the corresponding voice age / gender recognition deep neural network model is accurately selected to decode and determine the age and / or gender information of the target object, and the age and / or gender information is returned to the terminal. Due to the fact that the age and / or gender service mode and the remote calling architecture are set, the corresponding model is called after the type of the model is determined, calling is more accurate and does not need to depend on a fixed frame, the method is more flexible, expandability is high, the resource utilization rate is high, concurrency is high, and meanwhile iterative updating of the algorithm model is facilitated.
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Description

technical field

[0001] The present invention relates to the field of voice recognition, in particular to a method and system for realizing voice age and / or gender recognition. Background technique

[0002] The speech age and / or gender recognition model based on the Kaldi HMM-DNN hybrid architecture has great advantages in the ability to recognize speech, but it is very difficult to deploy and use in industry. The commonly used method is to first convert the KaldiNnet3 model through the model The tool is converted into an ONNX model, and then other deep learning engines are used to use the ONNX model to provide speech recognition services (for example: MACE mobile terminal AI computing engine), or to deploy using Tensorflow Serving, but the two methods used The framework is fixed and not easy to modify. For speech recognition services, it has poor flexibility and poor scalability, and only supports the operators of the Kaldi neural network reasoning part. WFST decoding still ...

Claims

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