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Keywords = virtual hall signal

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27 pages, 6147 KiB  
Article
Noise-Robust Multimodal Audio-Visual Speech Recognition System for Speech-Based Interaction Applications
by Sanghun Jeon and Mun Sang Kim
Sensors 2022, 22(20), 7738; https://doi.org/10.3390/s22207738 - 12 Oct 2022
Cited by 7 | Viewed by 3788
Abstract
Speech is a commonly used interaction-recognition technique in edutainment-based systems and is a key technology for smooth educational learning and user–system interaction. However, its application to real environments is limited owing to the various noise disruptions in real environments. In this study, an [...] Read more.
Speech is a commonly used interaction-recognition technique in edutainment-based systems and is a key technology for smooth educational learning and user–system interaction. However, its application to real environments is limited owing to the various noise disruptions in real environments. In this study, an audio and visual information-based multimode interaction system is proposed that enables virtual aquarium systems that use speech to interact to be robust to ambient noise. For audio-based speech recognition, a list of words recognized by a speech API is expressed as word vectors using a pretrained model. Meanwhile, vision-based speech recognition uses a composite end-to-end deep neural network. Subsequently, the vectors derived from the API and vision are classified after concatenation. The signal-to-noise ratio of the proposed system was determined based on data from four types of noise environments. Furthermore, it was tested for accuracy and efficiency against existing single-mode strategies for extracting visual features and audio speech recognition. Its average recognition rate was 91.42% when only speech was used, and improved by 6.7% to 98.12% when audio and visual information were combined. This method can be helpful in various real-world settings where speech recognition is regularly utilized, such as cafés, museums, music halls, and kiosks. Full article
(This article belongs to the Special Issue Future Speech Interfaces with Sensors and Machine Intelligence)
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6 pages, 961 KiB  
Article
A Novel Rectification Method for a High Level ac Voltage Converting to a Low Level dc Voltage: Example of Scooters Idling Stop System
by Pin-Yung Chen, Rongshun Chen, Yung-Chen Wang and Hsieh-Tai Su
World Electr. Veh. J. 2015, 7(3), 420-425; https://doi.org/10.3390/wevj7030420 - 25 Sep 2015
Viewed by 1089
Abstract
This paper proposed a novel rectification method for a high-level ac voltage convert to a low-level dc voltage, in which the Permanent Magnet Synchronous Motor (PMSM) Matlab/Simulink model in generation mode has been established in order to analyze the energy characteristics of PMSM [...] Read more.
This paper proposed a novel rectification method for a high-level ac voltage convert to a low-level dc voltage, in which the Permanent Magnet Synchronous Motor (PMSM) Matlab/Simulink model in generation mode has been established in order to analyze the energy characteristics of PMSM operating in scooters at full drive speed. From the simulation results, the terminal voltage and line current in load-side have a wide convert rate when the internal resistance of battery is a great value. In design, the gate driver signals can be generated, referring to the virtual hall signals, to chop the different back Electromotive Force (back-EMF). Then, the ac voltages of back-EMF can be rectified to the dc voltage by Metal Oxide Semiconductor Field Effect Transistors (MOSFETs) at the same time. Finally, the proposed method has been implemented in scooters idling stop system successfully, and a safe low level dc voltage always can be obtained to charge battery immediately (in general 12V) no matter what a variable speed in scooters. Full article
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