scholarly journals Which Utterance Types Are Most Suitable to Detect Hypernasality Automatically?

2021 ◽  
Vol 11 (19) ◽  
pp. 8809
Author(s):  
Ignacio Moreno-Torres ◽  
Andrés Lozano ◽  
Enrique Nava ◽  
Rosa Bermúdez-de-Alvear
Keyword(s):  
Mobile Devices ◽  
Selection Process ◽  
Mobile App ◽  
Classification Algorithms ◽  
Healthy Controls ◽  
Automatic Evaluation ◽  
Acoustic Features ◽  
Formant Frequency ◽  
Clinical Recommendations ◽  
Multiple Classifiers

Automatic tools to detect hypernasality have been traditionally designed to analyze sustained vowels exclusively. This is in sharp contrast with clinical recommendations, which consider it necessary to use a variety of utterance types (e.g., repeated syllables, sustained sounds, sentences, etc.) This study explores the feasibility of detecting hypernasality automatically based on speech samples other than sustained vowels. The participants were 39 patients and 39 healthy controls. Six types of utterances were used: counting 1-to-10 and repetition of syllable sequences, sustained consonants, sustained vowel, words and sentences. The recordings were obtained, with the help of a mobile app, from Spain, Chile and Ecuador. Multiple acoustic features were computed from each utterance (e.g., MFCC, formant frequency) After a selection process, the best 20 features served to train different classification algorithms. Accuracy was the highest with syllable sequences and also with some words and sentences. Accuracy increased slightly by training the classifiers with between two and three utterances. However, the best results were obtained by combining the results of multiple classifiers. We conclude that protocols for automatic evaluation of hypernasality should include a variety of utterance types. It seems feasible to detect hypernasality automatically with mobile devices.

Analysis and Resolution of Semantic Ambiguity of Toggle Buttons by Standardizing the Design in Software GUI and Mobile Apps

2017 ◽  
Vol 8 (2) ◽  
pp. 1-18
Author(s):  
Hongyu Guo ◽  
Amjad Nusayr ◽  
Wen-Chen Hu
Keyword(s):  
Mobile Devices ◽  
Current Practice ◽  
Mobile Apps ◽  
Mobile App ◽  
Semantic Ambiguity ◽  
Design Standards ◽  
Action Semantics

Toggle buttons are intuitive gadgets widely used in software GUI design and mobile app interfaces with increasing popularity on mobile devices. However, the current practice of toggle button design is prone to semantic ambiguity, which causes confusions to the users. This paper presents an analysis of the various paradigms of toggle button design in the current practice and provides a resolution of the sematic ambiguities by proposing a set of design standards regarding toggle buttons. State semantics and action semantics are distinguished and it is advocated that state semantics should be used in lieu of action semantics.

scholarly journals Parents welcome follow-up using mobile devices: A survey of acceptability at an Australian tertiary paediatric centre

2019 ◽  
Vol 47 (2) ◽  
pp. 189-192 ◽  
Author(s):  
Harry E Smallbone ◽  
Thomas FE Drake-Brockman ◽  
Britta S von Ungern-Sternberg
Keyword(s):  
Mobile Devices ◽  
Electronic Communication ◽  
Mobile Apps ◽  
Paediatric Population ◽  
Mobile App ◽  
Success Rates ◽  
Online Forms ◽  
Almost All ◽  
To Receive

Follow-up for ongoing management and monitoring of patients is important in clinical practice and research. While common, telephone follow-up is resource intensive and, in our experience, yields low success rates. Electronic communication using mobile devices including smartphones and tablets can provide efficient alternatives — including SMS (text), online forms and mobile apps. To assess attitudes towards electronic follow-up, we surveyed 642 parents and carers at Perth Children’s Hospital, targeting demographics, device ownership and attitudes towards electronic follow-up. Mobile phone ownership was effectively universal. Almost all respondents were happy to communicate electronically with the hospital. Promisingly, 93.2% of respondents were happy to receive follow-up SMSs from the hospital and 80.3% were happy to reply to SMS questions. There was less enthusiasm regarding other modalities, with 59.9% happy to use a website and 69.0% happy to use a mobile app. The results support the introduction of electronic communication for follow-up in our paediatric population.

scholarly journals Session Fingerprinting in Android via Web-to-App Intercommunication

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Efthimios Alepis ◽  
Constantinos Patsakis
Keyword(s):  
Mobile Devices ◽  
Context Awareness ◽  
Mobile Apps ◽  
Personal Data ◽  
Mobile App ◽  
Web Pages ◽  
Sensitive Information ◽  
Privacy Concerns ◽  
Everyday Lives

The extensive adoption of mobile devices in our everyday lives, apart from facilitating us through their various enhanced capabilities, has also raised serious privacy concerns. While mobile devices are equipped with numerous sensors which offer context-awareness to their installed apps, they can also be exploited to reveal sensitive information when correlated with other data or sources. Companies have introduced a plethora of privacy invasive methods to harvest users’ personal data for profiling and monetizing purposes. Nonetheless, up till now, these methods were constrained by the environment they operate, e.g., browser versus mobile app, and since only a handful of businesses have actual access to both of these environments, the conceivable risks could be calculated and the involved enterprises could be somehow monitored and regulated. This work introduces some novel user deanonymization approaches for device and user fingerprinting in Android. Having Android AOSP as our baseline, we prove that web pages, by using several inherent mechanisms, can cooperate with installed mobile apps to identify which sessions operate in specific devices and consequently further expose users’ privacy.

scholarly journals Utility of the Blood for Gene Expression Profiling and Biomarker Discovery in Chronic Fatigue Syndrome

2002 ◽  
Vol 18 (4) ◽  
pp. 193-199 ◽  
Author(s):  
Suzanne D. Vernon ◽  
Elizabeth R. Unger ◽  
Irina M. Dimulescu ◽  
Mangalathu Rajeevan ◽  
William C. Reeves
Keyword(s):  
Gene Expression ◽  
Chronic Fatigue Syndrome ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Biomarker Discovery ◽  
Chronic Fatigue ◽  
Classification Algorithms ◽  
Control Analysis ◽  
Healthy Controls ◽  
Fatigue Syndrome

Chronic fatigue syndrome (CFS) is a debilitating illness lacking consistent anatomic lesions and eluding conventional laboratory diagnosis. Demonstration of the utility of the blood for gene expression profiling and biomarker discovery would have implications into the pathophysiology of CFS. The objective of this study was to determine if gene expression profiles of peripheral blood mononuclear cells (PMBCs) could distinguish between subjects with CFS and healthy controls. Total RNA from PBMCs of five CFS cases and seventeen controls was labeled and hybridized to 1764 genes on filter arrays. Gene intensity values were analyzed by various classification algorithms and nonparametric statistical methods. The classification algorithms grouped the majority of the CFS cases together, and distinguished them from the healthy controls. Eight genes were differentially expressed in both an age-matched case-control analysis and when comparing all CFS cases to all controls. Several of the diffrentially expressed genes are associated with immunologic functions (e.g., CMRF35 antigen, IL-8, HD protein) and implicate immune dysfunction in the pathophysiology of CFS. These results successfully demonstrate the utility of the blood for gene expression profiling to distinguish subjects with CFS from healthy controls and for identifying genes that could serve as CFS biomarkers.

scholarly journals What should mobile app developers do about machine learning and energy?

2016 ◽  
Author(s):  
Andrea K McIntosh ◽  
Abram Hindle
Keyword(s):  
Machine Learning ◽  
Mobile Devices ◽  
Spatial Reasoning ◽  
Virtual Machines ◽  
Mobile App ◽  
Machine Learning Algorithms ◽  
Battery Life ◽  
Software Energy Consumption ◽  
Computationally Intensive ◽  
Learning Machine

Machine learning is a popular method of learning functions from data to represent and to classify sensor inputs, multimedia, emails, and calendar events. Smartphone applications have been integrating more and more intelligence in the form of machine learning. Machine learning functionality now appears on most smartphones as voice recognition, spell checking, word disambiguation, face recognition, translation, spatial reasoning, and even natural language summarization. Excited app developers who want to use machine learning on mobile devices face one serious constraint that they did not face on desktop computers or cloud virtual machines: the end-user’s mobile device has limited battery life, thus computationally intensive tasks can harm end-user’s phone availability by draining batteries of their stored energy. How can developers use machine learning and respect the limited battery life of mobile devices? Currently there are few guidelines for developers who want to employ machine learning on mobile devices yet are concerned about software energy consumption of their applications. In this paper we combine empirical measurements of many different machine learning algorithms with complexity theory to provide concrete and theoretically grounded recommendations to developers who want to employ machine learning on smartphones.

scholarly journals Analyzing of Customer Requirements to Eric Mobile Application

2018 ◽  
Vol 14 (2) ◽  
pp. 15-22
Author(s):  
Juraj Čamaj ◽  
Jaroslav Mašek ◽  
Martin Kendra
Keyword(s):  
Mobile Devices ◽  
Mobile Device ◽  
Mobile Application ◽  
Mobile App ◽  
Mobile Technologies ◽  
Customer Requirements ◽  
Application Development ◽  
Information Centre ◽  
Software Application ◽  
Basic Characteristics

Abstract Users in transport, forwarding and logistics companies use the mobile technologies for connect to existing information systems. By solving the ERIC Mobile project, these services will also be available on mobile devices. The article is aimed at lancing the requirements of all types of customers for the ERIC Mobile app. After the basic characteristics of the mobile device, the operation systems, the application development typology, the authors focus on the developing application “ERIC Mobile”. The aim of the article is to provide relevant requirements for further research and development of the software application of the rail freight information centre in Europe for end users of mobile devices such as smartphones and tablets.

scholarly journals Mobile Apps in Daily Learning Activities

2018 ◽  
Vol 12 (6) ◽  
pp. 133 ◽  
Author(s):  
Ivo Damyanov ◽  
Nikolay Tsankov
Keyword(s):  
Mobile Devices ◽  
Mobile Apps ◽  
Educational Games ◽  
Mobile App ◽  
School Education ◽  
Learning Activities ◽  
Smart Devices ◽  
Single Person ◽  
The Subject ◽  
Main Determinants

<span>The use of mobile devices is increasing in daily learning activities, providing single-person use combined with interactive learning materials, simulations, voice recognition and educational games. Mobile app stores bring to learners a large amount of mobile applications, but their value and effectiveness to support these learning activities is far from being adequately studied.</span><br /><span>In this paper, we present our recent study related to the opportunities for smart devices to be used in school education, outlining the main obstacles and challenges. The subject of the research is students' interest in the use of multimedia mobile devices for educational purposes. The aim of the study is to establish the main determinants for the complete and purposeful application of smart devices in school education.</span>

Acoustical-Perceptual Correlates of "Whisper Pitch" in Synthetically Generated Vowels

1999 ◽  
Vol 42 (3) ◽  
pp. 583-591 ◽  
Author(s):  
Masahiko Higashikawa ◽  
Fred D. Minifie
Keyword(s):  
Inverse Relationship ◽  
Acoustic Features ◽  
Vowel Production ◽  
Formant Frequency ◽  
Frequency Shifts ◽  
Male And Female ◽  
Formant Frequencies ◽  
Frequency Changes ◽  
40 Hz

The purpose of this investigation was to clarify acoustical-perceptual relationships in identification of "pitch" during whispered vowel production. The experimenters systematically varied selected acoustic features of synthetically generated "whispered" vowels to control which formant frequencies were shifted (F1, F2, or F1&F2), the direction of formant frequency shifts (up or down), and the magnitude of formant frequency shifts (20 Hz, 40 Hz, 60 Hz). Two sets of stimuli were produced to simulate the resonance characteristics of the vowel /a/: one set for male talkers and one for female talkers. Ninety-four pairs of synthesized vowel tokens were randomly presented to 17 listeners who judged if the "pitch" of the second member of the pair was the same, higher, or lower than the "pitch" of the first member. The results showed an inverse relationship between the magnitude of formant frequency changes presented to the judges and the number of perceptual mismatches in "whisper pitch." Also, fewer mismatches in the identification of whisper pitch occurred when both F1 and F2 were changed simultaneously than when either F1 or F2 was changed individually. No differences were found between the perceptual responses to "male" and "female" vowel simulations. The primary implication of this study is that whisper pitch is more influenced by simultaneous changes in F1 and F2 than by changes in only one of the formants.

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