Reference-Free Speech Quality Assessment for Mobile Phones Based on Audio Perception

Abstract

Speech quality evaluation is a very complex task with important applications. With the deployment of 3G and 4G networks, the end-user is requiring more quality of service. Currently, the assessment of speech quality over mobile phones is done in a controlled environment with a reference clean signal and its distorted version. However, this does not evaluate the quality of speech in a real-time situation as it demands a reference signal. In this paper, it is introduced a new method to classify a speech signal over a mobile device as distorted or not. The degraded signal is evaluated and its quality is scored similarly as what is done by PESQ (Perceptual Evaluation of Speech Quality). The experiments proved that the method is quite efficient with an average difference of 12% comparing to PESQ scores which is based on a reference clean signal.

Enhancement of the adaptive routing tensor model in the infocommunication network with providing quality of experience by the R-factor

“…To obtain in analytical form the conditions for providing QoE by the R-factor (8), a tensor description of the infocommunication network ( 11)-(28) was performed. This allowed to obtain analytical expressions for calculating the average end-to-end delay (26) and the probability of packet loss (27), which were used to form QoE conditions (8).…”

“…So, the use of subjective methods, which are described in [6,7], allows to evaluate the QoE level mainly only at the moment when the audio and video information is subjected to distortions that occur during digitization, compression, transmission, decoding, etc. For example, for a video stream, these methods are based on subjective metrics such as Single-Stimulus Continuous Quality Evaluation (SSCQE), Double Stimulus Impairment Scale (DSIS) and Double Stimulus Continuous Quality Scale (DSCQS) [8,9]. And for the subjective assessment of the audio stream, Perceptual Speech Quality Measurement (PSQM) mechanisms are usually used [10,11].…”

“…Thus, the problem of adaptive routing in the infocommunication network with the provision of QoE by the R-factor is formulated in the optimization form. The criterion for the optimality of route solutions was a minimum of linear form (29), and restrictions-expressions (1), (2), ( 4) and (8).…”

“…N = 30 The intensity of traffic coming to the network on the first router R 1 and intended for the ninth router R 9 was 350 1/s. Requirements for the level of QoE were set by the R-factor, according to expression (8) and data, according to [13,14], are shown in Table 1.…”

Speech Quality Classifier Model based on DBN that Considers Atmospheric Phenomena

“…Speech quality in a telecommunications system is considered an important parameter for assessing the user satisfaction [13]. It depends on different factors, such as network conditions, speech codec, environment noise, among others.…”