Artificial Neural Network based Automatic Speech Recognition Engine for Voice Controlled Micro Air Vehicles

Gowda, Sushma. M.; Rahul, D. K.; Anand, Anush; Veena, S.; Durdi, Vinod B

doi:10.1109/rteict46194.2019.9016983

Search citation statements

Order By: Relevance

Paper Sections

Select...

Related Work1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2021

2022

Publication Types

Select...

Preprint1

Book1

Other1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Focusing on voice control, [22] proposed voice control using an artificial neural network (ANN)-based automatic speech recognition (ASR) engine. They proposed a forwardfeed neural network-based speech recognition method for voice-controlled micro air vehicle (MAV) applications.…”

Section: Related Workmentioning

confidence: 99%

HoloGCS : Mixed Reality-based Ground Control Station for Unmanned Aerial Vehicle

Widiyanti¹,

Asmoro²,

Shin³

2022

Preprint

View full text Add to dashboard Cite

Ground control station (GCS) is a system for controlling and monitoring unmanned aerial vehicle (UAV). In current GCS, the device used are considered as complex environment. This paper proposes a video streaming and speech command control for supporting mixed reality based UAV GCS using Microsoft HoloLens. Video streaming will inform the UAV view and transmit the raw video to the HoloLens, while the HoloLens steers the UAV based on the displayed UAV field of view (FoV). Using the HoloLens Mixed Reality Tool-Kit (MRTK) speech input, UAV speech control from the HoloLens was successfully implemented. Finally, experimental results based on video streaming and speech command calculation of the throughput, round-time trip, latency and speech accuracy tests are discussed to demonstrate the feasibility of the proposed scheme.

show abstract

Section: Related Workmentioning

confidence: 99%