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The bits of silence
Author(s) -
Mohammad A. Hoque,
Petteri Nurmi,
Matti Siekkinen,
Pan Hui,
Sasu Tarkoma
Publication year - 2020
Publication title -
helda (university of helsinki)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-6845-2
DOI - 10.1145/3339825.3391854
Subject(s) - silence , computer science , voice over ip , codec , conversation , context (archaeology) , energy consumption , overhead (engineering) , microphone , telecommunications , speech recognition , computer network , engineering , the internet , electrical engineering , acoustics , paleontology , linguistics , philosophy , physics , sound pressure , world wide web , biology , operating system
Human conversation is characterized by brief pauses and so-called turn-taking behavior between the speakers. In the context of VoIP, this means that there are frequent periods where the microphone captures only background noise - or even silence whenever the microphone is muted. The bits transmitted from such silence periods introduce overhead in terms of data usage, energy consumption, and network infrastructure costs. In this paper, we contribute by shedding light on these costs for VoIP applications. We systematically measure the performance of six popular mobile VoIP applications with controlled human conversation and acoustic setup. Our analysis demonstrates that significant savings can indeed be achieved - with the best performing silence suppression technique being effective on 75% of silent pauses in the conversation in a quiet place. This results in 2-5 times data savings, and 50-90% lower energy consumption compared to the next best alternative. Even then, the effectiveness of silence suppression can be sensitive to the amount of background noise, underlying speech codec, and the device being used. The codec characteristics and performance do not depend on the network type. However, silence suppression makes VoIP traffic network friendly as much as VoLTE traffic. Our results provide new insights into VoIP performance and offer a motivation for further enhancements to a wide variety of voice assisted applications, such as home assistants and other IoT devices.

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