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Speech quality is often measured via subjective testing, or with objective estimators of mean opinion score (MOS) such as ViSQOL or POLQA. Typical MOS-estimation frameworks use signal level features but do not use language features that have been shown to have an effect on opinion scores. If there is a conditional dependence between score and language given these signal features, introducing language and rater predictors should provide a marginal improvement in predictions. The proposed method uses Bayesian models that predict the individual opinion score instead of MOS. Several models that test various combinations of predictors were used, including predictors that capture signal features, such as frequency band similarity, as well as features that are related to the listener, such as a language and rater index. The models are fit to the ITU-T P. Supplement 23 dataset, and posterior samples are drawn from distributions of both the model parameters and the resulting opinion score outcomes. These models are compared to MOS models by integrating over posterior samples per utterance. An experiment was conducted by ablating different predictors for several types of Bayesian hierarchical models (including ordered logistic and truncated normal individual score distributions, as well as MOS distributions) to find the marginal improvement of language and rater. The models that included language and/or rater obtained significantly lower errors (0.601 versus 0.684 root-mean-square error (RMSE)) and higher correlation. Additionally, individual rater models matched or exceeded the performance of MOS models.

Objective: Assessing the respiratory and lung mechanics of the patients in intensive care units is of utmost need in order to guide the management of ventilation support. The esophageal pressure (Peso) signal is a minimally invasive measure, which portrays the mechanics of the lung and the pattern of breathing. Because of the close proximity of the lung to the beating heart inside the thoracic cavity, the Peso signals always get contaminated with that of the oscillatory-pressure-signal of the heart, which is known as the cardiogenic oscillation (CGO) signal. However, the area of research addressing the removal of CGO from Peso signal is still lagging behind. Methods and results: This paper presents a singular spectrum analysis-based high-efficient, adaptive and robust technique for the removal of CGO from Peso signal utilizing the inherent periodicity and morphological property of the Peso signal. The performance of the proposed technique is tested on Peso signals collected from the patients admitted to the intensive care unit, cadavers, and also on synthetic Peso signals. The efficiency of the proposed technique in removing CGO from the Peso signal is quantified through both qualitative and quantitative measures, and the mean opinion scores of the denoised Peso signal fall under the categories `very good' as per the subjective measure. Conclusion and clinical impact: The proposed technique: (1) does not follow any predefined mathematical model and hence, it is data-driven, (2) is adaptive to the sampling rate, and (3) can be adapted for denoising other biomedical signals which exhibit periodic or quasi-periodic nature.

Forecasting weather and forewarning the public with weather alerts help save lives and property immensely. Audio transmissions for alerting are not prone to local infrastructure failure and hence the most dependable. Reception of such alerts should have good clarity of audio. The Mean Opinion Score (MOS) method has traditionally been used in telephony to monitor audio reception quality. It requires an objective skilled listener using a scoring system for feedback used in improving audio quality. However, in weather radio, there is no dedicated listener 24/7. Without listening skills and listener training the MOS scoring could be skewed and of little use. Our paper focuses on the design, building and testing of audio-quality forensics system (AQFS) that uses measurements of network, radio and equipment parameters to monitor audio quality instead of listener feedback. Transmitter stations today have multiple connectivity options and the AQFS can alert the transmission operators to switch to alternate technology during failures. The AQFS also has control features to perform this switching automatically that we have tested. In this paper, we also report our findings, test results and inferences with recommendations. Apart from providing basic but detailed audio quality analysis and comparison of base and transmitted audio using two different mechanisms, the AQFS helped us detect complete audio loss, intermittent audio outages, Specific Area Message Encoding (SAME) Headers, audio anomalies, fades, drops and strange tones which correlate with fading and outage events. The analysis helped at problem transmitter sites in improving audio quality.

One of the main goals of the future wireless networks is improving the users’ quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells’ base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs’ powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells’ antennas in the network leads to a higher user satisfaction. [ABSTRACT FROM AUTHOR]

Advancements in electronics and miniaturized device fabrication technologies have enabled simultaneous acquisition of multiple biosignals (MBioSigs), but the area of compression of MBioSigs remains unexplored to date. This paper presents a robust singular value decomposition (SVD) and American standard code for information interchange (ASCII) character encoding-based algorithm for compression of MBioSigs for the first time to the best of our knowledge. At the preprocessing stage, MBioSigs are denoised, down sampled and then transformed to a two-dimensional (2-D) data array. SVD of the 2-D array is carried out and the dimensionality of the singular values is reduced. The resulting matrix is then compressed by a lossless ASCII character encoding-based technique. The proposed compression algorithm can be used in a variety of modes such as lossless, with or without using the down sampling operation. The compressed file is then uploaded to a hypertext preprocessor (PHP)-based website for remote monitoring application. Evaluation results show that the proposed algorithm provides a good compression performance; in particular, the mean opinion score of the reconstructed signal falls under the category “very good” as per the gold standard subjective measure. [ABSTRACT FROM PUBLISHER]

How accurately are people able to use the absolute category rating (ACR) 5-level scale? Put another way, how repeatable are an individual subject’s scores? Several subjective experiments have asked subjects to rate the same sequences a couple of times. Analyses indicate that none of the subjects exactly repeated their prior scores for these sequences. We would like to better understand this imperfection. This paper uses ACR subjective video quality tests to explore the precision of subjective ratings. To make formal measurements possible, we propose a theoretical subject model that is the main contribution of this paper. The proposed subject model indicates three major factors that influence accuracy: subject bias, subject inaccuracy, and stimulus scoring difficulty. These appear to be separate random effects and their existence is a reason why none of the subjects were able to perfectly repeat scores. There are three key consequences. First, subject scoring behavior includes a random component that spans approximately half of the rating scale. Second, the sensitivity and accuracy of most subjective analyses can be improved if the subject scores are normalized by removing subject bias. Third, to some extent, multiple subjects can be replaced with a single subject who rates each sequence multiple times. [ABSTRACT FROM PUBLISHER]

Crowdsourcing has emerged in recent years as a potential strategy to enlist the general public to solve a wide variety of tasks. With the advent of ubiquitous Internet access, it is now feasible to ask an Internet crowd to conduct QoE (Quality of Experience) experiments on their personal computers in their own residences rather than in a laboratory. The considerable size of the Internet crowd allows researchers to crowdsource their experiments to a more diverse set of participant pool at a relatively low economic cost. However, as participants carry out experiments without supervision, the uncertainty of the quality of their experiment results is a challenging problem. [ABSTRACT FROM PUBLISHER]

In this letter, we propose a simple and efficient method, called `Dual-CRC', to improve speech quality based on the list Viterbi algorithm (LVA) in the Universal Mobile Telecommunications System (UMTS). We also employ the well-known joint source-channel decoding (JSCD) scheme together with LVA decoding to further improve the speech quality. Simulation results show that the two proposed decoders, the Dual-CRC LVA and the combination of the LVA and the JSCD, can significantly improve the speech quality for UMTS, especially in low signal-to-noise ratio and low mean opinion score regions. [ABSTRACT FROM PUBLISHER]

This article describes the activity performed in the three-year project “Integration of Multimedia Services on Heterogeneous Satellite Networks,” funded by the Italian Space Agency (ASI) and carried out by the Italian National Consortium for Telecommunications (CNIT). The description of the activity allows highlighting the problems, findings, and solutions in utilizing TCP/IP-based services and applications, such as audio-video transmission and Web browsing, via satellite channels. The article presents an experimental approach to provide QoS guarantees and to improve the performance of TCP over a satellite network based on the TCP/IP suite. The aim is to obtain a proper environment for data, voice, and video transmission oriented to a distance learning service that uses both audio-video applications and Web-based tools. The experimental scenario is made up of three remote LANs. Two of them are connected through a geostationary orbit satellite link in the Ka-band (20-30 GHz). The other LAN, located in a site where no satellite station is available, is connected through an ISDN link at 512 kb/s. Both subjective metrics such as mean opinion score and objective metrics such as throughput and overall transmission time have been used to evaluate the performance of the system and to get proper configurations able to guarantee a high QoS perceived by the users. The integrated services approach along with the resource reservation protocol were chosen to reserve the network resources at the IP level. A modified version of TCP has been proposed and utilized to reduce the download time during Web browsing and f.t.p. sessions. The measures reported have been obtained by real operative sessions [ABSTRACT FROM PUBLISHER]