AsQM: Audio Streaming Quality Metric Based on Network Impairments and User Preferences

Abstract

Audio streaming services have many users because the proliferation of cloud-based audio streaming services for different content. The complex networks that support these services do not always guarantee an acceptable quality on the end-user side. In this paper, the impact of temporal interruptions on the audio streaming reproduction and the user’s preference in relation to audio content are studied. In order to determine the key parameters in the audio streaming service, subjective tests are conducted, and their results show that a user’s quality-of-experience (QoE) is highly correlated with the following application parameters: the number of temporal interruptions or stalls, its frequency and length, and the temporal location where they occur. However, most important, the experimental results demonstrate that users’ preference for audio content plays an important role in users’ QoE. Thus, a preference factor (PF) function is defined and considered in the formulation of the proposed metric named audio streaming quality metric (AsQM). Considering that multimedia service providers are based on web servers, a framework to obtain user information is proposed. Furthermore, the results show that the AsQM implemented in the audio player of an end user’s device has a low impact on energy, processing and memory consumption.