AsQM: Audio streaming Quality Metric based on Network Impairments and User Preferences

TL;DR

This paper introduces AsQM, a new audio streaming quality metric that incorporates network impairments and user preferences, validated through subjective tests and designed to be resource-efficient for end-user devices.

Contribution

The paper proposes a novel audio quality metric, AsQM, integrating user preferences and network impairments, with a framework for collecting user data and low resource impact on devices.

Findings

AsQM correlates strongly with user QoE metrics.

User preferences significantly influence perceived audio quality.

The framework efficiently gathers user data with minimal resource use.

Abstract

There are many users of audio streaming services because of 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 reproduction of audio streaming and the users preference in relation to audio contents are studied. In order to determine the key parameters in the audio streaming service, subjective tests were conducted, and their results show that users 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 in which they occur. However, most important, experimental results demonstrated 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, results show that the AsQM implemented in the audio player of an end users device presents a low impact on energy, processing and memory consumption.