Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/49825
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dc.creatorRodríguez, Demóstenes Z.-
dc.creatorCarrillo, Dick-
dc.creatorRamírez, Miguel A.-
dc.creatorNardelli, Pedro H. J.-
dc.creatorMöller, Sebastian-
dc.date.accessioned2022-04-28T21:53:23Z-
dc.date.available2022-04-28T21:53:23Z-
dc.date.issued2021-02-
dc.identifier.citationRODRÍGUEZ, D. Z. et al. Incorporating Wireless Communication Parameters Into the E-Model Algorithm. IEEE/ACM Transactions on Audio, Speech, and Language Processing, [S. I.], v. 29, p. 956-968, 2021. DOI: 10.1109/TASLP.2021.3057955.pt_BR
dc.identifier.urihttps://ieeexplore.ieee.org/document/9351640pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/49825-
dc.description.abstractTelecommunication service providers have to guarantee acceptable speech quality during a phone call to avoid a negative impact on the users’ quality of experience. Currently, there are different speech quality assessment methods. ITU-T Recommendation G.107 describes the E-model algorithm, which is a computational model developed for network planning purposes focused on narrowband (NB) networks. Later, ITU-T Recommendations G.107.1 and G.107.2 were developed for wideband (WB) and fullband (FB) networks. These algorithms use different impairment factors, each one related to different speech communication steps. However, the NB, WB, and FB E-model algorithms do not consider wireless techniques used in these networks, such as Multiple-Input-Multiple-Output (MIMO) systems, which are used to improve the communication system robustness in the presence of different types of wireless channel degradation. In this context, the main objective of this study is to propose a general methodology to incorporate wireless network parameters into the NB and WB E-model algorithms. To accomplish this goal, MIMO and wireless channel parameters are incorporated into the E-model algorithms, specifically into the Ie,eff and Ie,eff,WB impairment factors. For performance validation, subjective tests were carried out, and the proposed methodology reached a Pearson correlation coefficient (PCC) and a root mean square error (RMSE) of 0.9732 and 0.2351, respectively. It is noteworthy that our proposed methodology does not affect the rest of the E-model input parameters, and it intends to be useful for wireless network planning in speech communication services.pt_BR
dc.languageenpt_BR
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)pt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceIEEE/ACM Transactions on Audio, Speech, and Language Processingpt_BR
dc.subjectE-modelpt_BR
dc.subjectMultiple-Input-Multiple-Output (MIMO)pt_BR
dc.subjectMIMO system E-modelpt_BR
dc.subjectPacket losspt_BR
dc.subjectSpeech quality assessmentpt_BR
dc.subjectWireless communicationpt_BR
dc.subjectMúltiplas Entradas e Múltiplas Saídaspt_BR
dc.subjectQualidade vocal - Avaliaçãopt_BR
dc.subjectComunicação sem fiopt_BR
dc.titleIncorporating Wireless Communication Parameters Into the E-Model Algorithmpt_BR
dc.typeArtigopt_BR
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