Abstract
By just a looking it, It’s hard for us to know if hearing impaired people have obstacles. Therefore, Hearing impaired people cannot understand of the circumstances, and they cannot get supports enough. They often live without telling they have obstacles people around them themselves. The purpose of this study, we will develop the system that visually notifies the dangerous sounds generated outside the visual field. We construct the database of environmental sounds, and select the dangerous sound from the environmental sound. This system checks the waveform data and dangerous sound database, and displays danger on the monitor if it meets conditions such as volume and distance from the source. This system displays characters using “realistic fonts” that we have developed from before, that is the expression method expressing the feeling of sound using manga technique. In this study, we will report outline of this research and a prototype of our system. We record the sound supposed to be dangerous sounds with variety of directions and range from sound source using microphone array. And we compare the waveform data for each microphone recorded, and verify the features. This system identifies three kinds of sounds and displays using realistic fonts reflecting volume and direction of sound source.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Dahl GE, Yu D et al (2011) Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition. IEEE Trans Audio Speech Lang Process 20(1):30–42
Arai H, Ido T et al. (2017) Events and sounds that hearing impaired persons feel dangerous. The 18th Asia Pacific industrial engineering and management systems conference (APIEMS 2017), pp F5–1, F5–5
Oh H, Kashiwa K et al. (2013) Method for visualization of moving image sound in the context of onomatopoeic animation. In: Workshop on interactive systems and software, Anthology of Theses, pp 165–166 (in Japanese)
Hinton G, Deng L et al (2012) Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups. IEEE Signal Process Mag 29(6):82–97
Tanaka J, Tatsumi T et al (2001) Analysis of shoes sound. Trans JSME 67(657):1303–1308 (in Japanese)
Takamiya K, Okamoto M (2009) The interaction for deaf people to recognize environmental sound. Bull Jpn Soc Sci Design 56:110–111 (in Japanese)
Kawamoto M, Asano F, Kurumaya K (2008) Search system for detection of dangerous situations and extraordinary daily life sounds to watch over the sound environment through use of microphone arrays. Information Processing Society of Japan (UBI) research report 66:19–26
Matsuzaki J (2017) Study on construction of support system using speech recognition application. Bull Res Center Inf Process Miyagi Univ Educ 24:3–8 (in Japanese)
Hiraga R, Kato Y et al (2017) A learning system for deaf and hard-of-hearing children-prototype and future plans-Techno Report of National University Corporation Tsukuba University of Technology 24(2):17–21 (in Japanese)
Seto S, Arai H et al.(2011) Visualization of non-verbal expressions in voice by using manga technique-ambient font for hearing impaired student
Seto S, Arai H et al. (2010) Subtitle system visualizing non-verbal expressions in voice for hearing impaired–Ambient Font–. Deakin University
Unserschutz G (2011) Language as the visual: exploring the intersection of linguistic and visual language in manga. Image Narrat Online Mag Visual Narrat 12(1):167–188
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Arai, H., Ido, T., Shimomura, Y., Kawabe, H., Nambo, H., Seto, S. (2019). A System that Warns of Dangerous Environmental Sounds for the Hearing Impaired. In: Xu, J., Cooke, F., Gen, M., Ahmed, S. (eds) Proceedings of the Twelfth International Conference on Management Science and Engineering Management. ICMSEM 2018. Lecture Notes on Multidisciplinary Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-93351-1_89
Download citation
DOI: https://doi.org/10.1007/978-3-319-93351-1_89
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-93350-4
Online ISBN: 978-3-319-93351-1
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)