Two-Dimensional Convolutional Recurrent Neural Networks for Speech Activity Detection

Speech Activity Detection (SAD) plays an important role in mobile communications and automatic speech recognition (ASR). Developing efficient SAD systems for real-world applications is a challenging task due to the presence of noise. We propose a new approach to SAD where we treat it as a two-dimensional multilabel image classification problem. To classify the audio segments, we compute their Short-time Fourier Transform spectrograms and classify them with a Convolutional Recurrent Neural Network (CRNN), traditionally used in image recognition. Our CRNN uses a sigmoid activation function, max-pooling in the frequency domain, and a convolutional operation as a moving average filter to remove misclassified spikes. On the development set of Task 1 of the 2019 Fearless Steps Challenge, our system achieved a decision cost function (DCF) of 2.89%, a 66.4% improvement over the baseline. Moreover, it achieved a DCF score of 3.318% on the evaluation dataset of the challenge, ranking first among all submissions

Μοντελοποίηση και σχεδιασμός μετωπικών οδοντωτών τροχών παραλλήλων αξόνων με υπερ-υψηλή γωνίας πίεσης και εφαρμογή σε πλανητικούς μειωτήρες.

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Συστήματα Αυτοματισμού

ArchGenTool: a System-Independent Collaborative Tool for Robotic Architecture Design

Complex robotic architectures require a collaborative effort in design and adherence to the design in the implementation phse. ArchGentTool is a collaborative architecture generation tool which supports the design of the robotic architecture in a multi-level fashion. It comprises high-level conceptual analysis of the system to be designed, as well as low-level implementation breakdown of its functional components, acting complementary to the ROS framework. The tool facilitates reusability and expandability of the architecture to any robotic system, as it can be adapted to different specifications. A case study with the RAMCIP service robot is presente

Comparing CNN and Human Crafted Features for Human Activity Recognition

Deep learning techniques such as Convolutional Neural Networks (CNNs) have shown good results in activity recognition. One of the advantages of using these methods resides in their ability to generate features automatically. This ability greatly simplifies the task of feature extraction that usually requires domain specific knowledge, especially when using big data where data driven approaches can lead to anti-patterns. Despite the advantage of this approach, very little work has been undertaken on analyzing the quality of extracted features, and more specifically on how model architecture and parameters affect the ability of those features to separate activity classes in the final feature space. This work focuses on identifying the optimal parameters for recognition of simple activities applying this approach on both signals from inertial and audio sensors. The paper provides the following contributions: (i) a comparison of automatically extracted CNN features with gold standard Human Crafted Features (HCF) is given, (ii) a comprehensive analysis on how architecture and model parameters affect separation of target classes in the feature space. Results are evaluated using publicly available datasets. In particular, we achieved a 93.38% F-Score on the UCI-HAR dataset, using 1D CNNs with 3 convolutional layers and 32 kernel size, and a 90.5% F-Score on the DCASE 2017 development dataset, simplified for three classes (indoor, outdoor and vehicle), using 2D CNNs with 2 convolutional layers and a 2x2 kernel size

Improving the application of the Integrated River Basin Management paradigm in the implementation of the EU Water Framework Directive

The European Union’s (EU) Water Framework Directive (WFD) was adopted to succeed and replace traditional management practices and is widely accepted as the most substantial piece of European environmental legislation to date. Despite some good progress in its implementation, 47% of EU surface waters haven’t reached good ecological status in 2015, a central objective of the Directive. Policy analysis of the Directive’s interpretation and application by Member States, demonstrated the absence of the paradigm shift towards the systems thinking, as a fundamental problem with its implementation. This was also evident in cases where the Directive had been criticised as a policy tool indicating misunderstandings even of its core principles. Reviewing the transition of EU water policies towards the WFD revealed that different interpretations on the Directive’s objectives and exemptions had been left unresolved since its negotiation, ambiguity and compromises observed by its Common Implementation Strategy and lack of real support for the policy shift required, to have all been barriers to the harmonised transposition of the Integrated River Basin Management paradigm, the key to delivering good ecological status. A study of the implementation efforts of the five case study basins of the EU project GLOBAQUA further supported this. Analysis at one of these case studies, investigated whether the way the measures were developed could have limited their potential to deliver WFD objectives and showed that measures were designed to target element classifications, rather than to manage catchment pressures. Incorporating Ecosystem Services as indicators of impacts, a participatory framework for pressure prioritisation was developed that could support the development of measures and stakeholder acceptance and commitment to policy decisions. Overall, the research undertaken demonstrated the need to return to the initial aspirations of the WFD, revisit the concepts it embraced and explore ways to operationalise them if to deliver environmental improvements.Open Acces

Feature extraction based on bio-inspired model for robust emotion recognition

Emotional state identification is an important issue to achieve more natural speech interactive systems. Ideally, these systems should also be able to work in real environments in which generally exist some kind of noise. Several bio-inspired representations have been applied to artificial systems for speech processing under noise conditions. In this work, an auditory signal representation is used to obtain a novel bio-inspired set of features for emotional speech signals. These characteristics, together with other spectral and prosodic features, are used for emotion recognition under noise conditions. Neural models were trained as classifiers and results were compared to the well-known mel-frequency cepstral coefficients. Results show that using the proposed representations, it is possible to significantly improve the robustness of an emotion recognition system. The results were also validated in a speaker independent scheme and with two emotional speech corpora.Fil: Albornoz, Enrique Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Rufiner, Hugo Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

The transition of EU water policy towards the Water Framework Directive’s Integrated River Basin Management paradigm

Introduced in 2000 to reform and rationalise water policy and management across the European Union (EU) Member States (MS), the Water Framework Directive (WFD), the EU’s flagship legislation on water protection, is widely acknowledged as the embodiment and vessel for the application of the Integrated River Basin Management (IRBM) paradigm. Its ecological objectives, perhaps even more challenging than the prospect of statutory catchment planning itself, were for all EU waters to achieve ‘good status’ by 2015 (except where exemptions applied) and the prevention of any further deterioration. In support of the upcoming WFD review in 2019, the paper reviews the transition of EU policies that led to the adoption of the WFD, to identify the reasons why the Directive was introduced and what it is trying to deliver, and to place progress with its implementation into context. It further investigates reasons that might have limited the effectiveness of the Directive and contributed to the limited delivery and delays in water quality improvements. Findings reveal that different interpretations on the Directive’s objectives and exemptions left unresolved since its negotiation, ambiguity and compromises observed by its Common Implementation Strategy and lack of real support for the policy shift required have all been barriers to the harmonised transposition of the IRBM paradigm, the key to delivering good ecological status. The 2019 WFD review offers a unique opportunity to realign the implementation of the Directive to its initial aspirations and goals

From Detection to Action Recognition: An Edge-Based Pipeline for Robot Human Perception

Mobile service robots are proving to be increasingly effective in a range of applications, such as healthcare, monitoring Activities of Daily Living (ADL), and facilitating Ambient Assisted Living (AAL). These robots heavily rely on Human Action Recognition (HAR) to interpret human actions and intentions. However, for HAR to function effectively on service robots, it requires prior knowledge of human presence (human detection) and identification of individuals to monitor (human tracking). In this work, we propose an end-to-end pipeline that encompasses the entire process, starting from human detection and tracking, leading to action recognition. The pipeline is designed to operate in near real-time while ensuring all stages of processing are performed on the edge, reducing the need for centralised computation. To identify the most suitable models for our mobile robot, we conducted a series of experiments comparing state-of-the-art solutions based on both their detection performance and efficiency. To evaluate the effectiveness of our proposed pipeline, we proposed a dataset comprising daily household activities. By presenting our findings and analysing the results, we demonstrate the efficacy of our approach in enabling mobile robots to understand and respond to human behaviour in real-world scenarios relying mainly on the data from their RGB cameras.Comment: 7 pages, 10 figures, 2 table

Progress with monitoring and assessment in the wfd implementation in five european river basins: Significant differences but similar problems

Copyright © 2018 The Authors. The river basin approach of the Water Framework Directive (WFD) and the introduction of ecological status represent a shift in the assessment and management of freshwater systems from discipline-specific to more holistic, catchment-based principles. At the core of the WFD’s approach are catchments as highly interconnected systems. Despite strict timetables, progress towards achieving the WFD objectives has been slow, with deterioration in some cases not being halted. In this paper, looking at evidence from five European basins (Adige, Anglian, Ebro, Evrotas and Sava) we identify some of the key implementation challenges faced by each catchment during the development and implementation of the 1st River Basin Management Plans (RBMPs) of 2009. Despite significant differences in socio-ecological conditions, geographic coverage and starting points in the implementation between these river basins, findings highlight some similar key issues. The lack of a common systemic understanding of each river basin and detailed monitoring data to capture pressure-status interactions in order to anticipate how the system will react to interventions; as well as compliance driven implementation efforts were underlying problems in all five study areas. While some improvements to address these problems can be seen in the 2nd River Basin Management Planning Cycle (2015–2016), our findings demonstrate that a more effective approach is to question the deviation of the whole implementation from the directive’s systemic nature and therefore improve the adaptive, collaborative, participatory and interdisciplinary nature of the implementation efforts.European Communities 7th Framework Programme Funding under Grant agreement no. 603629-ENV-2013-6.2.1-GLOBAQUA

A participatory ecosystems services approach for pressure prioritisation in support of the Water Framework Directive

Research data for this article: The data are provided as supplementary material available online at: https://www.sciencedirect.com/science/article/pii/S2212041618303486?via%3Dihub#s0050 .Copyright © 2018 The Authors. The pressure and impact analysis is an important process in integrated river basin management and a key procedural element of the EU Water Framework Directive. It aims to inform both the assessment of water body status and the development of management responses. However, the Directive does not provide prescriptive guidance on how it should be carried out and during the 1st river basin cycle, its application proved to be a real challenge. Incorporating ecosystem services as indicators of impacts, a participatory framework for pressure prioritisation is presented here. While various methods exist for engaging stakeholders in river basin management, the framework allows for the ecosystem approach to be operationalised through a risk assessment perspective, in the context of the pressure impact analysis. Applying this to a case study in England, we demonstrate how a ranking of pressures can be delivered based on stakeholders’ perception of how the delivery of ecosystem services is affected by each pressure and incorporating their value as indicator of the magnitude of the impact. This approach allows for a more systematic way to effectively prioritise significant pressures and therefore select appropriate programmes of measures in line with the Directive’s integrated river basin management paradigm.European Union’s Seventh Programme for research, technological development, and demonstration under grant agreement no. 603629-ENV-2013-6.2.1-Globaqua and the NERC funded project A Novel Framework for Predicting Emerging Chemical Stressor Impacts in Complex Ecosystems, NERC Reference: NE/S000348/1