A universal data transfer technique over voice channels of cellular mobile communication networks

Zhang, Tikui; Yu, Bin

doi:10.1049/cmu2.12047

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…Previously, it has been used in applications such as audio data compression [44], voice encryption [45], voice modification [46] and even as an electronic musical instrument [47]. Researchers have adapted it as a tool to simulate the operation of a cochlear implant.…”

Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants

Henry,

Parsi,

Glavin

et al. 2023

Sensors

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Although cochlear implants work well for people with hearing impairment in quiet conditions, it is well-known that they are not as effective in noisy environments. Noise reduction algorithms based on machine learning allied with appropriate speech features can be used to address this problem. The purpose of this study is to investigate the importance of acoustic features in such algorithms. Acoustic features are extracted from speech and noise mixtures and used in conjunction with the ideal binary mask to train a deep neural network to estimate masks for speech synthesis to produce enhanced speech. The intelligibility of this speech is objectively measured using metrics such as Short-time Objective Intelligibility (STOI), Hit Rate minus False Alarm Rate (HIT-FA) and Normalized Covariance Measure (NCM) for both simulated normal-hearing and hearing-impaired scenarios. A wide range of existing features is experimentally evaluated, including features that have not been traditionally applied in this application. The results demonstrate that frequency domain features perform best. In particular, Gammatone features performed best for normal hearing over a range of signal-to-noise ratios and noise types (STOI = 0.7826). Mel spectrogram features exhibited the best overall performance for hearing impairment (NCM = 0.7314). There is a stronger correlation between STOI and NCM than HIT-FA and NCM, suggesting that the former is a better predictor of intelligibility for hearing-impaired listeners. The results of this study may be useful in the design of adaptive intelligibility enhancement systems for cochlear implants based on both the noise level and the nature of the noise (stationary or non-stationary).

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Section: Introductionmentioning

confidence: 99%

Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants

Henry,

Parsi,

Glavin

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…With the rapid development of 5G wireless communication technologies and the rapid popularization of various mobile terminals, many huge networks formed by tens of thousands of mobile devices have risen. Those mobile devices in the Internet of things (IoT) such as mobile phones, tablets, smartwatches, POS terminals, and onboard computers, naturally have the characteristic of random movement due to they are carried by users [1][2][3]. When communication occurs, they consist of a system that can abstract out some of the characteristics of human networks [4].…”

Section: Introductionmentioning

confidence: 99%

“…(1) We first formulate the problem of dividing nodes into several communities in the opportunistic social network as how to build communities dynamically according to weight distribution (2) In order to solve time complexity and decrease overhead costs for communication in the opportunistic social network, we propose the data delivery strategy based on the stochastic block model and community detection (DDBSC) on the basis of considering the nonuniformity of community (3) We compare the proposed algorithm with four advanced routing algorithms. The simulation results show that the proposed DDBSC outperforms the other four algorithms in terms of overhead, energy consumption, and delivery ratio…”

Section: Introductionmentioning

confidence: 99%

Modified Data Delivery Strategy Based on Stochastic Block Model and Community Detection in Opportunistic Social Networks

Gou

2022

Wireless Communications and Mobile Computing

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The nodes in the opportunistic network make up communities according to the relevance between them. Some of the structural characteristics of an opportunistic network can be reflected by the structure of the communities that exist in the network. Therefore, finding community from the network is of great significance for people to better study, use, and transform the network. The overlap of communities is considered to be an important feature of communities. Almost all community discovery algorithms were based on nonoverlapping communities in the past. A node in a nonoverlapping community belongs to only one community. However, there are overlapping and interrelated characteristics between communities, so it is not in line with the actual environment of the network. As a result, the previous algorithms have many shortcomings in the face of practical application scenarios, coupled with the limitation of the computing capacity of mobile devices; data transmission for low delay and the low energy consumption is difficult to meet the requirements. In the study, we formulate the problem of dividing nodes into several communities in the opportunistic social network as how to build communities dynamically according to weight distribution. Then, we propose a modified data delivery strategy based on stochastic block model and community detection (DDBSC). The simulation results show that, compared with other algorithms in the experiments, the strategy proposed in this paper exhibits good performance in terms of overhead, energy consumption, and delivery rate.

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Introducing a Novel Data Over Voice Technique for Secure Voice Communication

Krasnowski¹,

Martin²,

Lebrun³

2022

Wireless Pers Commun

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The current increasing need for privacy-preserving voice communications is leading to new ideas for securing voice transmission. This paper refers to a relatively new concept of sending encrypted data or speech as pseudo-speech in the audio domain over existing voice communication infrastructures, like 3G cellular network and Voice over IP (VoIP). The distinctive characteristic of such a communication system is that it relies on the robust transmission of binary information in the form of audio signal. This work presents a novel Data over Voice (DoV) technique based on codebooks of short harmonic waveforms. The technique provides a sufficiently fast and reliable data rate over cellular networks and many VoIP applications. The new method relies on general principles of Linear Predictive Coding for voice compression (LPC voice coding) and is more versatile compared to solutions trained on exact channel models. The technique gives by design a high control over the desired rate of transmission and provides robustness to channel distortion. In addition, an efficient codebook design approach inspired by quaternary error correcting codes is proposed. The usability of the proposed DoV technique for secure voice communication over cellular networks and VoIP has been successfully validated by empirical experiments. The paper details the system parameters, putting a special emphasis on system's security and technical challenges.

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A universal data transfer technique over voice channels of cellular mobile communication networks

Cited by 5 publications

References 20 publications

Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants

Experimental Investigation of Acoustic Features to Optimize Intelligibility in Cochlear Implants

Modified Data Delivery Strategy Based on Stochastic Block Model and Community Detection in Opportunistic Social Networks

Introducing a Novel Data Over Voice Technique for Secure Voice Communication

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