Abstract
Earphones and headphones are devices that are very widely used these days for a number of purposes. Whether it be to listen to your favorite songs or watch a movie, we all end up using either device at some point or the other during our days. Especially with the COVID-19 pandemic that struck us last year, we have all been confined to our homes for the most part. This leads to an increase in the usage of such devices. We have often found ourselves bored and feel like watching a movie or feeling quite blue and end up listening to our all-time favorite songs. It has become an essential part of our daily lives at this point. With the COVID-19 pandemic starting from 2020, there has been a significant rise in the number of people purchasing wearable earphones, headphones, and other audio devices. A study conducted by the International Data Corporation showed a 144.3% YoY growth in available earwear devices in 2020. A study conducted by the team at boAt also shows that their company saw significant growth in terms of their products which were purchased by consumers like us during the pandemic period. Earphones and headphones are available from a plethora of brands and in a wide range of prices depending upon our requirements. Despite all these differences in specific models and brands, one thing that all earphones/headphones have in common is the fact that they are designed to provide a higher level of isolation from our surrounding environment compared to hearing the same media through our basic loudspeakers. Now it is also known that people prefer higher levels of isolation while listening to different media that they are willing to pay a higher price for achieving it, and manufacturers also capitalize on this knowledge. There are special models of earphones with Noise Canceling Technology—which further isolates the user from hearing barely anything going on in their surroundings. There are positives to this aspect—yes, but there are also negatives to this. Suppose a user, listening to audio using Noise Canceling headphones, is being called out to by somebody in their vicinity in the event of an emergency. This particular aspect makes it extremely difficult to alert the user and can even be a threat to their own lives. Our proposed system aims to combat this problem by using a relatively simple technology of voice recognition software combined with preexisting hardware in the user's device.
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References
Ghosh, D., Balaji, K., & Paramasivam, P. (2015). A method to alert user during headset playback by detection of horn in real time. In 2015 IEEE Recent Advances in Intelligent Computational Systems (RAICS) (pp. 50–54). https://doi.org/10.1109/RAICS.2015.7488387.
Xia, S., et al. (2019). Improving pedestrian safety in cities using intelligent wearable systems. IEEE Internet of Things Journal, 6(5), 7497–7514. https://doi.org/10.1109/JIOT.2019.2903519
Basu, S., Clarkson, B., & Pentland, A. (2001). Smart headphones: enhancing auditory awareness through robust speech detection and source localization. In 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221) (Vol. 5, pp. 3361–3364). https://doi.org/10.1109/ICASSP.2001.940379.
Das, S., Banerjee, D., Kundu, S., Das, S., Kumar, S., & Ghosh, G. (2017). A new idea on road safety using smartphone. In 2017 1st International Conference on Electronics, Materials Engineering and Nano-Technology (IEMENTech) (pp. 1–4). https://doi.org/10.1109/IEMENTECH.2017.8077002.
Chen, Y., Argentinis, J. D. E., & Weber, G. (2016). IBM Watson: how cognitive computing can be applied to big data challenges in life sciences research. Clinical Therapeutics, 38(4), 688–701. https://doi.org/10.1016/j.clinthera.2015.12.001.
Anggraini, N., et al. (2018). Speech recognition application for the speech impaired using the android-based google cloud speech API. Telkomnika, 16(6), 2733–2739. https://doi.org/10.12928/telkomnika.v16i6.9638.
Jadhav, S., Karpe, S., & Das, S. (2021). Sound classification using python. In ITM Web of Conferences (Vol. 40). EDP Sciences. https://doi.org/10.1051/itmconf/20214003024.
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D’Souza, J.D., Anand, V.S., Madhu, A., Renjith, S. (2023). MuteMe—An Automatic Audio Playback Controller During Emergencies. In: Noor, A., Saroha, K., Pricop, E., Sen, A., Trivedi, G. (eds) Proceedings of Emerging Trends and Technologies on Intelligent Systems. Advances in Intelligent Systems and Computing, vol 1414. Springer, Singapore. https://doi.org/10.1007/978-981-19-4182-5_10
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DOI: https://doi.org/10.1007/978-981-19-4182-5_10
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