scholarly journals A Review of Emotion Recognition Methods Based on Data Acquired via Smartphone Sensors

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6367 ◽  
Author(s):  
Agata Kołakowska ◽  
Wioleta Szwoch ◽  
Mariusz Szwoch
Keyword(s):  
Emotion Recognition ◽  
High Efficiency ◽  
Complex Data ◽  
Emotional States ◽  
Learning Approaches ◽  
Computing Services ◽  
Sufficient Power ◽  
Main Computer ◽  
Smartphone Sensors ◽  
Cloud Computing Services

In recent years, emotion recognition algorithms have achieved high efficiency, allowing the development of various affective and affect-aware applications. This advancement has taken place mainly in the environment of personal computers offering the appropriate hardware and sufficient power to process complex data from video, audio, and other channels. However, the increase in computing and communication capabilities of smartphones, the variety of their built-in sensors, as well as the availability of cloud computing services have made them an environment in which the task of recognising emotions can be performed at least as effectively. This is possible and particularly important due to the fact that smartphones and other mobile devices have become the main computer devices used by most people. This article provides a systematic overview of publications from the last 10 years related to emotion recognition methods using smartphone sensors. The characteristics of the most important sensors in this respect are presented, and the methods applied to extract informative features on the basis of data read from these input channels. Then, various machine learning approaches implemented to recognise emotional states are described.

scholarly journals Generalisation and robustness investigation for facial and speech emotion recognition using bio-inspired spiking neural networks

2021 ◽  
Vol 25 (3) ◽  
pp. 1717-1730
Author(s):  
Esma Mansouri-Benssassi ◽  
Juan Ye
Keyword(s):  
Facial Expression ◽  
Emotion Recognition ◽  
Affective Computing ◽  
Third Party ◽  
Speech Emotion Recognition ◽  
Expression Recognition ◽  
Emotional States ◽  
Learning Approaches ◽  
Feature Representations ◽  
The Face

AbstractEmotion recognition through facial expression and non-verbal speech represents an important area in affective computing. They have been extensively studied from classical feature extraction techniques to more recent deep learning approaches. However, most of these approaches face two major challenges: (1) robustness—in the face of degradation such as noise, can a model still make correct predictions? and (2) cross-dataset generalisation—when a model is trained on one dataset, can it be used to make inference on another dataset?. To directly address these challenges, we first propose the application of a spiking neural network (SNN) in predicting emotional states based on facial expression and speech data, then investigate, and compare their accuracy when facing data degradation or unseen new input. We evaluate our approach on third-party, publicly available datasets and compare to the state-of-the-art techniques. Our approach demonstrates robustness to noise, where it achieves an accuracy of 56.2% for facial expression recognition (FER) compared to 22.64% and 14.10% for CNN and SVM, respectively, when input images are degraded with the noise intensity of 0.5, and the highest accuracy of 74.3% for speech emotion recognition (SER) compared to 21.95% of CNN and 14.75% for SVM when audio white noise is applied. For generalisation, our approach achieves consistently high accuracy of 89% for FER and 70% for SER in cross-dataset evaluation and suggests that it can learn more effective feature representations, which lead to good generalisation of facial features and vocal characteristics across subjects.

Cloud Computing in Library

2014 ◽  
Vol 3 ◽  
pp. 94-112
Author(s):  
Angelė Pečeliūnaitė
Keyword(s):  
Cloud Computing ◽  
Scientific Community ◽  
Digital Age ◽  
International Experience ◽  
The Internet ◽  
Library Services ◽  
General Activity ◽  
Computing Services ◽  
Cloud Computing Services

The article analyses the possibility of how Cloud Computing can be used by libraries to organise activities online. In order to achieve a uniform understanding of the essence of technology SaaS, IaaS, and PaaS, the article discusses the Cloud Computing services, which can be used for the relocation of libraries to the Internet. The improvement of the general activity of libraries in the digital age, the analysis of the international experience in the libraries are examples. Also the article discusses the results of a survey of the Lithuanian scientific community that confirms that 90% of the scientific community is in the interest of getting full access to e-publications online. It is concluded that the decrease in funding for libraries, Cloud Computing can be an economically beneficial step, expanding the library services and improving their quality.

One Implementation Method of Trust Evaluation Tool Used on Cloud Computing Service

2019 ◽  
Vol 12 (3) ◽  
pp. 223-231
Author(s):  
Shengju Yang
Keyword(s):  
Cloud Computing ◽  
Access Control ◽  
Service Providers ◽  
Assessment Method ◽  
Trust Evaluation ◽  
Evaluation Tool ◽  
Computing Services ◽  
Business Goals ◽  
Cloud Computing Service ◽  
Cloud Computing Services

In order to solve the trust problems between users and cloud computing service providers in cloud computing services, the existing trust evaluation technology and access control technology in the cloud computing service are analyzed. And the evaluation index of cloud computing is also analyzed. Users can calculate the relevant indicators of cloud computing service according to their own business goals, and choose the appropriate cloud computing services according to their own trust need. In addition, the reliability assessment method of users based on the service process is proposed. Cloud computing access control system can be used for user credibility evaluation, and it can handle user access requests according to user's creditability. In the study, a cloud computing service trust evaluation tool is designed, and the modeling and architecture designs of trust evaluation are also given. The effectiveness of the method is verified by experiments on cloud computing service evaluation methods.

scholarly journals Producing ‘good enough’ automated transcripts securely: Extending Bokhove and Downey (2018) to address security concerns

2021 ◽  
Vol 14 (1) ◽  
pp. 205979912098776
Author(s):  
Joseph Da Silva
Keyword(s):  
Cyber Security ◽  
English Language ◽  
Negative Impact ◽  
Early Career ◽  
Third Party ◽  
Doctoral Research ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Audio Data

Interviews are an established research method across multiple disciplines. Such interviews are typically transcribed orthographically in order to facilitate analysis. Many novice qualitative researchers’ experiences of manual transcription are that it is tedious and time-consuming, although it is generally accepted within much of the literature that quality of analysis is improved through researchers performing this task themselves. This is despite the potential for the exhausting nature of bulk transcription to conversely have a negative impact upon quality. Other researchers have explored the use of automated methods to ease the task of transcription, more recently using cloud-computing services, but such services present challenges to ensuring confidentiality and privacy of data. In the field of cyber-security, these are particularly concerning; however, any researcher dealing with confidential participant speech should also be uneasy with third-party access to such data. As a result, researchers, particularly early-career researchers and students, may find themselves with no option other than manual transcription. This article presents a secure and effective alternative, building on prior work published in this journal, to present a method that significantly reduced, by more than half, interview transcription time for the researcher yet maintained security of audio data. It presents a comparison between this method and a fully manual method, drawing on data from 10 interviews conducted as part of my doctoral research. The method presented requires an investment in specific equipment which currently only supports the English language.

Cloud computing services, models and simulation tools

2021 ◽  
Vol 10 (5/6) ◽  
pp. 533
Author(s):  
Moulhime El Bekkali ◽  
Benaissa Bernoussi ◽  
Mohammed Fattah ◽  
Said Mazer ◽  
Younes Balboul ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Simulation Tools ◽  
Computing Services ◽  
Cloud Computing Services
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