Incorporating Wireless Communication Parameters Into the E-Model Algorithm

Autor(es)

Rodriguez, Demostenes Z. ^[1] ; Carrillo, Dick ^[2] ; Ramirez, Miguel A. ^[3] ; Nardelli, Pedro H. J. ^[2] ; Moeller, Sebastian ^{[4, 5]}

Afiliação do(s) autor(es)

^[1] Univ Fed Lavras, BR-37200900 Lavras - Brazil

^[2] LUT Univ, Sch Energy Syst, Yliopistonkatu 53850 34 - Finland

^[3] Univ Sao Paulo, Escola Politecn, Dept Elect Syst Engn, BR-05508010 Sao Paulo - Brazil

^[4] Tech Univ Berlin, Qual & Usabil Lab, D-10623 Berlin - Germany

^[5] Deutsch Forsch Zentrum Kunstliche Intelligenz DFK, D-67663 Kaiserslautern - Germany

• Tipo de documento: Artigo Científico
• Fonte: IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING; v. 29, p. 956-968, 2021.
• Citações Web of Science: 0

Resumo

Telecommunication 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 I-e,I-eff and I-e,I-eff,(W) (B) 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. (AU)

• Processo FAPESP: 18/26455-8 - Processamento Audiovisual de Voz por Aprendizagem de Máquina
• Beneficiário: Miguel Arjona Ramírez
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 15/24496-0 - Avaliação do serviço das operadoras de comunicações utilizando o índice de qualidade de voz
• Beneficiário: Demostenes Zegarra Rodriguez
• Modalidade de apoio: Auxílio à Pesquisa - Regular