Ergonomic improvement using natural language processing for voice-directed order selection in large industrial settings

Abstract

This field study examined the automatic speech recognition (ASR) of voice-directed computerized systems for order selectors employed in large industrial settings (e.g., fulfillment centers, distribution centers, warehouses, and manufacturing plants). Voice-directed systems for order selection require selectors to listen to instructions via a headset and speak into a microphone, directing each worker to select products for store orders throughout the facility. Originally, ASR used voice recognition that required “voice enrollment” (voice setup) for each worker plus a trainer's time required as part of the setup. Voice setup generally averaged about 60 min for both the worker and the trainer. Lately, a newer technology now utilizes “speech recognition,” which eliminates voice enrollment altogether. This study measured order selector voice setup times between voice recognition and speech recognition in five facilities. In two distribution centers where speech recognition was implemented, all voice setup hours for all order selectors (n = 55) plus the trainer's time were eliminated. This amounted to a total savings of 110 h. Moreover, using speech recognition becomes a recurring saving for each new employee entering the organization. Now the focus of training is shifted from voice setup to immediately training workers to select orders via voice, an ergonomic improvement.