An Automatic Emergency Signal Recognition System for the Hearing Impaired

Beritelli, Francesco; Casale, S.; Russo, Alessandra; Serrano, Salvatore

doi:10.1109/dspws.2006.265438

Cited by 26 publications

(20 citation statements)

References 5 publications

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“…G. Albertengo et al, in cooperation with Telecom Italia, integrated the Bluetooth diagnostic device and GPS by using ELM327 to detect the arrival and departure of vehicles [4]. Among related researches on specific audio recognition, F. Beritelli et al adopted the Fast Fourier Transform and Mel-Frequency Cepstral Coefficients to help the hearing impaired recognize emergency warning signals sent by tow trucks, police cars, ambulances and fire trucks [5]. Regarding the application of on-board sensors, J. Dai et al detected the abnormal turns caused by drunk driving with the accelerometer and according to the ratios reflected by specific driving data [6].…”

Section: Related Workmentioning

confidence: 99%

Design and Implement of App Based OBD-II Vehicle Tracking System

2016

Proceedings of 2016 the 6th International Workshop on Computer Science and Engineering

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The fleet management service identifies the driver behavior pattern, restricts improper operation and avoids trouble-making actions or deviant behavior to save operation costs. The fleet management system architecture mostly depends on hardware driving recorders to obtain relevant data. However, the hardware system is not easy to customize, expand or adjust due to its fixed data categories and system functions. Therefore, by integrating OBD-II and smart phones, this paper proposes developing a software vehicle tracking system with an algorithm to detect vehicle-environment interactive behaviors based on Android, an open source software stack. This system aims to collect various information from vehicles and mobile phone sensors, identify interactive behavior, provide the back-end vehicle management system for monitoring and analysis, improve traditional fleet management in terms of customization, expansion and real-time performance, and facilitate fast-speed establishment and customization of the driving management system.

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Section: Related Workmentioning

confidence: 99%

Design and Implement of App Based OBD-II Vehicle Tracking System

2016

Proceedings of 2016 the 6th International Workshop on Computer Science and Engineering

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“…The current research that has been done on audio recognition all deals with supervised training systems, such systems are discussed in the next couple paragraphs. Beritelli et al [2006] designed a system that was used for the purposes of identifying emergency signals for the hearing impaired. This system was designed for the purpose of identifying what type of emergency vehicle was approaching and notifying the hearing impaired individual of what was happening.…”

Section: Security Considerationsmentioning

confidence: 99%

Towards A Universally Usable Human Interaction Proof

Sauer

Lazar

Hochheiser

et al. 2010

ACM Trans. Access. Comput.

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The need for security features to stop spam and bots has prompted research aimed at developing human interaction proofs (HIPs) that are both secure and easy to use. The primarily visual techniques used in these HIP tools present difficulties for users with visual impairments. This article reports on the development of Human-Interaction Proof, Universally Usable (HIPUU), a new approach to human-interaction proofs based on identification of a series of sound/image pairs. Simultaneous presentation of a single, unified task in two alternative modalities provides multiple paths to successful task completion. We present two alternative task completion strategies, based on differing input strategies (menu-based vs. free text entry). Empirical results from studies involving both blind and sighted users validate both the usability and accessibility of these differing strategies, with blind users achieving successful task completion rates above 90%. The strengths of the alternate task completion strategies are discussed, along with possible approaches for improving the robustness of HIPUU.

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“…The scheme for recognize police vehicles, towing vehicles, fire engines, and ambulances was proposed [4]. In the voice recognition methods, the sound signal is transformed from the time domain to the frequency domain.…”

Section: Introductionmentioning

confidence: 99%

Recognition of the Ambulance Siren Sound in Taiwan by the Longest Common Subsequence

Liaw

Wang

Chu

et al. 2013

2013 IEEE International Conference on Systems, Man, and Cybernetics

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This paper proposes a method to recognize the ambulance siren sound in Taiwan. Since the ambulance siren sound is composed by a high frequency and a low frequency signal, the sequence of the frequency change is used to be the feature of the sound. The input sound is divided into frames, and each frame is classified into high frequency or low frequency. The Longest Common Subsequence (LCS) is used to compare the arrangement of the frequencies in the frames. We use the results of LCS to recognize whether the sound comes from an ambulance. Real sounds are used to show the performance. According to the experimental results, the accuracy rate is 85

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An Automatic Emergency Signal Recognition System for the Hearing Impaired

Cited by 26 publications

References 5 publications

Design and Implement of App Based OBD-II Vehicle Tracking System

Design and Implement of App Based OBD-II Vehicle Tracking System

Towards A Universally Usable Human Interaction Proof

Recognition of the Ambulance Siren Sound in Taiwan by the Longest Common Subsequence

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