Sign language translation method based on BP neural network

Abstract

The invention discloses a sign language translation method based on a BP neural network. The sign language translation method is characterized by comprising the following steps: 1, acquiring a gesturevoltage signal by utilizing Raspberry Pi 3B through a wearable data glove; 2, compiling sign language words and common sign language sentences corresponding to each group of gesture voltage signals into a sign language sentence library by utilizing a signal screening program; 3, writing a neural network classification program comprising a BP neural network structure framework model, a data transmission module and a storage module, wherein the BP neural network structure framework model adopts a three-layer neural network comprising an input layer, an output layer and a hidden layer; 4, converting the gesture voltage signals received each time into sign language words through a BP neural network framework model; and 5, converting the sign language words obtained in the step 4 into sign language word groups within a period of time, matching the sign language word groups with a sign language statement library, associating and filling into sentences, and outputting a result. According tothe invention, automatic real-time translation identification of sign language is realized by combining a neural network and a sensing technology.

Description

technical field [0001] The invention relates to a sign language translation method, and in particular discloses a BP neural network-based sign language translation method, which realizes sign language automatic translation recognition in combination with the neural network and sensing technology. Background technique [0002] In the process of communication between the deaf-mute and normal people in today's society, because normal people cannot understand sign language, there is a gap between the deaf-mute and normal people, which limits the communication circle of the deaf-mute and brings great space for their life and development. Big restrictions. There are two types of assistive devices for deaf-mute people on the market today. One is the electronic larynx that started in the 1950s. It is installed at the larynx joint to sense the vibration of the vocal cords and amplify it to help vocalization. However, the materials used to produce voices are expensive, and generally ...

AI Technical Summary

Problems solved by technology

[0002]In the process of communication between the deaf-mute and normal people in the society, because normal people cannot understand sign language, there is a gap between the deaf-mute and normal people, which limits the deaf-mute The social circle of mute people brings great restrictions to their life and development space

There are two types of assistive devices for deaf-mute people on the market today. One is the electronic larynx that started in the 1950s. It is installed at the larynx joint to sense the vibration of the vocal cords and amplify it to help vocalization. However, the materials used for vocalization are expensive, and generally disabled people without social work protection cannot afford them at all.

The other is sign language translation equipment based on computer vision that has appeared in the past few years. This type of equipment is not expensive, but the body movement recognition technology is still in its infancy, and image processing has strict requirements on the acquisition environment.

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