IBGS: A Wearable Smart System to Assist Visually Challenged

Abstract

Traditional blind guide devices are expensive and large. In this study, an intelligent blind guide system (IBGS) was introduced. GD32 is used as the main control chip, it cooperates with various functional modules to realize traffic light recognition, obstacle avoidance, payment, and navigation functions on the basis of speech recognition. At the same time, IBGS uses WIFI instead of Bluetooth to get rid of the dependence on smart phones. In addition, a cloud database was built, and the Internet of Things technology was used to realize the information interconnection between the IBGS, database, and the guardian’s mobile terminal. In order to better realize the function of speech recognition, this paper proposes a Conv-Transformer Transducer (ConvT-T) speech recognition framework based on Weak-Attention Suppression (WAS), which improves the efficiency of multi-head attention through WAS. The proposed method achieved a word error rate (WER) of 3.2% in test-clean and 7.9% in test-other on the LibriSpeech ASR corpus with only 73M parameters, which reduces the WER by 0.3% and 0.4% compared to ConvT-T respectively, indicating that WAS can effectively play the role of suppressing non-critical attention on the ConvT-T framework. At the same time, the IBGS was tested in a comprehensive application scenario. In the outdoor traffic light recognition, speech recognition, and obstacle avoidance tests, the accuracy rates were 92.33%, 90.33%, and 96.67% respectively. The results show that the IBGS can effectively deal with various challenges encountered by the blind during their daily outdoor walking.

Keywords

• Visually impaired
• wearable device
• traffic light recognition
• speech recognition