VoIP Quality Prediction Model by Bio-Inspired Methods

Book chapter abstract

ผู้เขียน/บรรณาธิการ

กลุ่มสาขาการวิจัยเชิงกลยุทธ์

ไม่พบข้อมูลที่เกี่ยวข้อง

รายละเอียดสำหรับงานพิมพ์

รายชื่อผู้แต่ง: Triyason T., Valaisathien S., Vanijja V., Kanthamanon P., Chan J.H.

ผู้เผยแพร่: Hindawi

ปีที่เผยแพร่ (ค.ศ.): 2015

หน้าแรก: 95

หน้าสุดท้าย: 116

จำนวนหน้า: 22

ISBN: 9780128017432; 9780128015384

นอก: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944392109&doi=10.1016%2fB978-0-12-801538-4.00005-7&partnerID=40&md5=d711ab213985936e2cfc7679288b2d22

ภาษา: English-Great Britain (EN-GB)

ดูบนเว็บไซต์ของสำนักพิมพ์

บทคัดย่อ

Voice over Internet Protocol (VoIP) quality measurement modeling is an active field of research. An objective and nonintrusive approach is preferred because it is faster and easier than a subjective or intrusive method. This chapter provides a brief overview of the bio-inspired methods used thus far in VoIP speech quality modeling. Then it compares several models such as Perceptual Evaluation of Speech Quality (PESQ)/E-model, nonlinear surface regression, neural network, and REPTree to model the conversational quality. Simulated data sets are generated by varying network impairments (packet loss and delay), codecs, languages, and gender to build and test the models. The bio-inspired neural network and the decision-tree-based REPTree models show highly reliable results for both network and nonnetwork impairment cases. In addition, the accuracy of the model is not only dependent on codec and network impairment, but the nonnetwork factors also have an impact on the performance of a speech quality prediction model. ฉ 2015 Elsevier Inc. All rights reserved.

คำสำคัญ

Bio-inspired, Nonintrusive