Method for accelerating running speed of translation software in small intelligent mobile equipment

Abstract

The invention discloses a method for accelerating the running speed of translation software in small intelligent mobile equipment. The method comprises the following steps of: 1) training two neural machine translation models based on a self-attention mechanism, including a large model and a small model; 2) constructing a parameter generator of which the input is the parameter of the large model and the output is the parameter of the small model, and transmitting knowledge in the parameter of the large model to the small model through a training parameter generator to complete a knowledge migration process; 3) decoding the small model to obtain a decoding result of the machine translation model, and proving the practical value of the small model; and 4) applying the small model to the small intelligent mobile device to realize the application of rapid decoding. According to the method, the advantage that knowledge of a large model is transferred to a small model through knowledge migration is fully utilized, the method can be achieved on the basis of the model with the best current performance, and on the premise that the performance of the model is hardly reduced, model compression is achieved, and the real-time corresponding speed is increased.

Description

technical field [0001] The invention relates to a neural machine translation model compression and acceleration technology, in particular to a method for accelerating the running speed of translation software in a small intelligent mobile device. Background technique [0002] Small smart mobile devices have become an indispensable source of knowledge for people. Due to people's demand for various types of applications, various APP software is frequently downloaded and stored by users of small smart mobile devices, resulting in the problem of small smart mobile devices lagging. Simply increasing the capacity of small smart mobile devices will lead to high hardware costs and increase the economic burden of users. Therefore, from another perspective, the space occupied by APP software on small smart mobile devices should be reduced as much as possible. [0003] Machine translation has a wide range of application requirements at this stage, and intelligent translation software i...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the problem that the machine translation model in the prior art is too large to be deployed on small devices with limited storage resources and computing resources, the technical problem to be solved by the present invention is to provide a method to speed up the running speed of translation software in small smart mobile devices. The method, making full use of the advantages of knowledge transfer that can transfer large model knowledge to small models, can realize model compression and improve real-time response speed on the basis of the realization of the current strongest model, and under the premise that the model performance is almost not degraded

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