Abstract
This paper discusses the reduction of background noise in an industrial environment to extend human-machine-interaction. In the Industry 4.0 era, the mass development of voice control (speech recognition) in various industrial applications is possible, especially as related to augmented reality (such as hands-free control via voice commands). As Industry 4.0 relies heavily on radiofrequency technologies, some brief insight into this problem is provided, including the Internet of things (IoT) and 5G deployment. This study was carried out in cooperation with the industrial partner Brose CZ spol. s.r.o., where sound recordings were made to produce a dataset. The experimental environment comprised three workplaces with background noise above 100 dB, consisting of a laser/magnetic welder and a press. A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from Microsoft. We tested a hybrid algorithm for noise reduction and its impact on voice command recognition efficiency. Using virtual devices, the study was carried out on large speakers with 20 participants (10 men and 10 women). The experiments included a large number of repetitions (100 times for each command under different noise conditions). Statistical results confirmed the efficiency of the tested algorithms. Laser welding environment efficiency was 27% before applied filtering, 76% using the least mean square (LMS) algorithm, and 79% using LMS + independent component analysis (ICA). Magnetic welding environment efficiency was 24% before applied filtering, 70% with LMS, and 75% with LMS + ICA. Press workplace environment efficiency showed no success before applied filtering, was 52% with LMS, and was 54% with LMS + ICA.
Highlights
Spoken word is still one of the most natural ways to directly transfer information between people [1,2]
Direct voice interaction with computers and machinery is slowly gaining in importance, as the industry is shifting towards the Industry 4.0 concept [3]
To carry out a reliable acoustic analysis requires the complete elimination of background noise, since it significantly influences the results
Summary
Spoken word is still one of the most natural ways to directly transfer information between people [1,2]. Voice communication systems are increasingly integrated into both industry and private life due to their significant benefits. Most applications are currently limited to a small set of tasks performed by specific machines using predetermined commands that they can recognize [4]. These systems are useful when the operator must do several things at once. Control takes place between the device and the local gateway by power line communication (PLC), Transmission Control Protocol (TCP), or Message Queue Telemetry Transport (MQTT) protocol, which enables control through suitable clients (e.g., a smartphone or Amazon Alexa) [5]
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