Quality Estimation (QE) is the task of predicting the quality of the output of Natural Language Processing (NLP) applications without relying on human references. This is a very appealing method for language output applications, i.e. applications that take as input a text and produce a different text as output, for example, Machine Translation, Text Summarisation and Text Simplification. For th...

We present a novel approach for speech-quality prediction based on the observation that perception-relevant properties may cover a wide range of different values without significantly changing perceptual quality. To account for this nonlinear phenomenon, a semi-supervised discretization concept is proposed which is applied to temporal as well as aggregated properties as a preprocessing step pri...

Recognizer Output Voting Error Reduction (ROVER) has been widely used for system combination in automatic speech recognition (ASR). In order to select the most appropriate words to insert at each position in the output transcriptions, some ROVER extensions rely on critical information such as confidence scores and other ASR decoder features. This information, which is not always available, high...

Inferring evaluation scores based on human judgments is invaluable compared to using current evaluation metrics which are not suitable for real-time applications e.g. post-editing. However, these judgments are much more expensive to collect especially from expert translators, compared to evaluation based on indicators contrasting source and translation texts. This work introduces a novel approa...

We describe the DCU-MIXED and DCUSVR submissions to the WMT-14 Quality Estimation task 1.1, predicting sentencelevel perceived post-editing effort. Feature design focuses on target-side features as we hypothesise that the source side has little effect on the quality of human translations, which are included in task 1.1 of this year’s WMT Quality Estimation shared task. We experiment with featur...

In the software Quality to predict the good quality of the programs or the software module is required for software quality estimation. This paper represents that track and detection of potential software faults near the beginning, which is critical in many high assurance systems. On the other hand, creating such accurate quality-estimation design is challenging because the data with noise and ...

Translation quality estimation is a task of growing importance in NLP, due to its potential to reduce post-editing human effort in disruptive ways. However, this potential is currently limited by the relatively low accuracy of existing systems. In this paper, we achieve remarkable improvements by exploiting synergies between the related tasks of word-level quality estimation and automatic post-...

To provide statistical guarantees of QoS, the Internet requires a measurement infrastructure for estimating available resources from actual tra c. In this paper, we outline an algorithm that collects a histogram of the occupancy of a single-server FCFS queue at packet arrival times, and infers the loss rate and delay distribution from such measurements. Direct estimation of such QoS parameters ...

the application of a flight simulator with six degree of freedom (6dof)) in design and analysis of rocket systems is essential. the calibration of a 6dof flight simulator is a challenging problem. this paper focuses on the calibration of a flight simulator and intends to answer the following questions: 1) does experimental design have significant impact on calibration quality? if so, which expe...