## 1 Introduction  
Since the invention of the telephone, voice-based telecommunication has been widely adopted. Audio communication involves audio signal capturing, processing, and transmission. The receiving end processes the received signal to output the reconstructed captured/original audio signal. This process introduces audio degradation. The introduced degradation affects the quality of service offered to users. Therefore, there is high interest in monitoring audio quality, mainly when the audio is transmitted over an Internet protocol (IP) network, the most commonly used global network. The IP network is a best-effort delivery network whereby the network does not guarantee that data are delivered or meet any quality of service, as the network performance depends entirely on the traffic load. Audio quality degradation in IP audio systems is introduced by environmental noise, poor network quality, and audio encoding-decoding algorithms. The quality of audio signals in IP networks depends much on the network's performance at a given instant. In VoIP applications such as telephone and video conferences involving two-way communications between humans, when the audio signal deteriorates, the involved parties can easily notice the situation and take mitigation measures. However, in some IP audio applications, such as PA systems, Internet radio, and music streaming apps, the communication is always one way, from the transmitter to the receivers. There is no way for the transmitter to know the quality at the receiver end. Therefore, there is a need for an automatic quality evaluation of the transmitted audio. Speech quality monitoring in VoIP systems enables autonomous system adaptation, e.g., changing encoding parameters or re-announcing. Furthermore, the IP network is shared with other applications. Hence, monitoring can detect when the network is overloaded and automatically switch to low-bitrate encoding. For a long time, voice over IP (VoIP) has been the main form of audio communication in IP networks. An increase in IP network bandwidth, decrease in cost, and increase in the accessibility of the IP network has enabled the introduction of more IP audio services such as Internet radios and music streaming applications. Currently, voice/speech and music are the major categories of audio transmitted over IP networks. Music and speech share common audio signal characteristics but have different objectives for listeners. High-quality speech and music audio signals should be of the same fidelity as the source after processing and transmission. Moreover, for speech communication, how easy it is to understand words utterances in the received speech audio signal after processing is very important. This measure is called intelligibility. Speech quality measures assess a speaker's utterance voice quality, including attributes such as natural, raspy, hoarse, scratchy, and so on. Speech quality is highly subjective and difficult to evaluate reliably because individual listeners have different standards of what constitutes good or poor quality, resulting in large variations in rating scores among listeners listening to the same audio. Intelligibility measures assess \"what words the speaker said\" compared to the \"words the listener heard\"; that is, the meaning or the content of the spoken words understood by the listener. Unlike speech quality, speech intelligibility is not subjective. It can be easily measured by presenting speech material (sentences, words, etc.) to a group of listeners and asking them to identify the words spoken. Intelligibility is quantified by counting the number of words or phonemes identified correctly. The relationship between speech intelligibility and speech quality is not fully understood. This is partly because we have not yet identified the acoustic correlations between quality and intelligibility [1]. Speech can be highly intelligible yet be of poor quality. Speech audio quality assessment can be performed using subjective listening tests or objective measures.