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A Real-Time Audio Compression Technique Based on Fast Wavelet Filtering and Encoding

Nella Romano, Antony Scivoletto, Dawid Połap
2016 Proceedings of the 2016 Federated Conference on Computer Science and Information Systems  
introducing a significant impairment in signal quality for listeners.  ...  In particular, we compare this innovative compression method with a typical VoIP encoding of human voice, underlining how using wavelet filters may be convenient, mainly in terms of compression rate, without  ...  WAVELETS In recent years, wavelet theory has been developed as a unifying framework for a large number of techniques for wave signal processing applications, such as multiresolution analysis, sub-band  ... 
doi:10.15439/2016f296 dblp:conf/fedcsis/RomanoSP16 fatcat:uqnynbjizfdlpj6epkdifl3yjq

A Single-Processor Approach to Speech Processing Pipeline of Bilateral Cochlear Implants [article]

Taher Shahbazi Mirzahasanloo
2014 arXiv   pre-print
This framework not only allows the design of environment-optimized parameters but also enables a user-specific solution where the anthropometric measurements of an individual user are incorporated into  ...  Its non-synchronization feature as well as low computational and memory requirements make it a suitable solution for actual deployment.  ...  Additionally, there remain a number of system-level extensions and open research studies in clinical evaluations of the developed framework, including subjective evaluations by hearing impaired CI users  ... 
arXiv:1409.6554v1 fatcat:tcqtneaqprd2fkobycnm3zp2oq

Table of contents

2014 2014 International Conference on Informatics, Electronics & Vision (ICIEV)  
Reusability 253 Interference Declination for Dynamic Channel Borrowing Scheme in Wireless Networks 255 Vibration and Voice Operated Navigation System for Visually Impaired Person 258 LVQ AND HOG  ...  Based on Noise Compensated Magnitude Spectrum 384 Path Planning Algorithm Development for Autonomous Vacuum Cleaner Robots 386 Content Based News Recommendation System Based on Fuzzy Logic 392 Unified  ...  Implementation of vision based intelligent home automation and security system. 436 Analysis of the local frequency spectrum for the chirp signal 439 An Review of the e-JIKEI Network: Security camera system  ... 
doi:10.1109/iciev.2014.6850868 fatcat:y4gdctlg3zgajc3ge3drl6itcy

Feature Selection Based on L1-Norm Support Vector Machine and Effective Recognition System for Parkinson's disease Using Voice Recordings

Amin Ul Haq, Jianping Li, Muhammad Hammad Memon, Jalaluddin khan, Asad Malik, Tanvir Ahmad, Amjad Ali, Shah Nazir, Ijaz Ahad, Mohammad Shahid
2019 IEEE Access  
In addition, the metrics of performance measures, such as accuracy, sensitivity, specificity, precision, F1 score, and execution time, were computed for model performance evaluation.  ...  The L1-norm SVM produced a new subset of features from the PD dataset based on a feature weight value. For the validation of the proposed system, the K -fold cross-validation method was used.  ...  [21] proposed framework for prediction of PD.  ... 
doi:10.1109/access.2019.2906350 fatcat:bg5v6543pfg4ziflxj6vwcy4jm

Multi-speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network [article]

Ravi Shankar and Hsi-Wei Hsieh and Nicolas Charon and Archana Venkataraman
2020 arXiv   pre-print
We propose a novel method for emotion conversion in speech based on a chained encoder-decoder-predictor neural network architecture.  ...  The encoder constructs a latent embedding of the fundamental frequency (F0) contour and the spectrum, which we regularize using the Large Diffeomorphic Metric Mapping (LDDMM) registration framework.  ...  This is done by learning a latent embedding based on the Large Diffeomorphic Metric Mapping (LDDMM) [15, 16] framework.  ... 
arXiv:2007.12937v2 fatcat:czm6v3yjnbavnhl4nlr4p6xf3e

Multi-Speaker Emotion Conversion via Latent Variable Regularization and a Chained Encoder-Decoder-Predictor Network

Ravi Shankar, Hsi-Wei Hsieh, Nicolas Charon, Archana Venkataraman
2020 Interspeech 2020  
We propose a novel method for emotion conversion in speech based on a chained encoder-decoder-predictor neural network architecture.  ...  The encoder constructs a latent embedding of the fundamental frequency (F0) contour and the spectrum, which we regularize using the Large Diffeomorphic Metric Mapping (LDDMM) registration framework.  ...  This is done by learning a latent embedding based on the Large Diffeomorphic Metric Mapping (LDDMM) [15, 16] framework.  ... 
doi:10.21437/interspeech.2020-1323 dblp:conf/interspeech/ShankarHCV20 fatcat:rdwi37gsjffsnidfqlblltlsuq

Enhancing Parkinson's Disease Diagnosis Accuracy Through Speech Signal Algorithm Modeling

Omar M. El-Habbak, Abdelrahman M. Abdelalim, Nour H. Mohamed, Habiba M. Abd-Elaty, Mostafa A. Hammouda, Yasmeen Y. Mohamed, Mohanad A. Taifor, Ali W. Mohamed
2022 Computers Materials & Continua  
To solve this issue, the study proposes using machine learning and deep learning models to analyze processed speech signals of patients' voice recordings.  ...  This research calls for a revolutionary diagnostic approach in decision support systems, and is the first step in a market-wide implementation of healthcare software dedicated to the aid of clinicians  ...  Ahmed Kamal for their invaluable insight, constructive feedback, and undying support throughout the whole duration of this arduous research.  ... 
doi:10.32604/cmc.2022.020109 fatcat:nevmvgsvtjb2tfjltm2au5pbnm

Alzheimer's disease and automatic speech analysis: a review

María Luisa Barragán Pulido, Jesús Bernardino Alonso Hernández, Miguel Ángel Ferrer Ballester, Carlos Manuel Travieso González, Jiří Mekyska, Zdeněk Smékal
2020 Expert systems with applications  
Automatic speech analysis, within the Health 4.0 framework, offers the possibility of assessing these patients, without the need for a specific infrastructure, by means of non-invasive, fast and inexpensive  ...  The objective of this paper is to present the state of-the-art relating to automatic speech and voice analysis techniques as applied to the monitoring of patients suffering from Alzheimer's disease as  ...  For the research, infrastructure of the SIX Center was used.  ... 
doi:10.1016/j.eswa.2020.113213 fatcat:usojapbmqngdbgwu366grza7hy

A Novel Approach for Parkinson's Disease Detection Based on Voice Classification and Features Selection Techniques

Asmae Ouhmida, Abdelhadi Raihani, Bouchaib Cherradi, Oumaima Terrada
2021 International Journal of Online and Biomedical Engineering (iJOE)  
In the current paper, a comparative analysis was performed on machine learning (ML) techniques for PD identification based on voice disorders analysis.  ...  The efficiency of the developed model has been evaluated based on accuracy, sensitivity, specificity and AUC metrics, and it is higher than existing approaches.  ...  Our approach is based on feature learning for an automatic identification of Parkinson's Disease using voice recording analysis.  ... 
doi:10.3991/ijoe.v17i10.24499 doaj:76fd7239786e4aa6a3b86bc68b7dc4cd fatcat:lspuk2mcmjbixclnunqqnotszy

A comparative and comprehensive study of prediction of Parkinson's disease

N. Prasath, Vigneshwaran Pandi, Sindhuja Manickavasagam, Prabu Ramadoss
2021 Indonesian Journal of Electrical Engineering and Computer Science  
In order to increase the precision approaches involving movements, facial expression and other attributes also be considered for evaluation  ...  Conclusion and Future work: Most of the methods have used speech as a major attribute for their research and have produced substantial accuracy.  ...  various sorts of voice information base.  ... 
doi:10.11591/ijeecs.v23.i3.pp1748-1760 fatcat:a2mlp3vn6ffcvjwubvilia47fe

A unified algorithm framework for quality control of sensor data for behavioural clinimetric testing [article]

Reham Badawy, Yordan P. Raykov, Max A. Little
2017 arXiv   pre-print
To address these problems, we report on a unified algorithmic framework for automated sensor data quality control, which can identify those parts of the sensor data which are sufficiently reliable for  ...  The approach is general enough to be applied to a large set of clinimetric tests and we demonstrate its performance on walking, balance and voice smartphone-based tests, designed to monitor the symptoms  ...  The authors gratefully acknowledge Andong Zhan for developing the smartphone application used in this study.  ... 
arXiv:1711.07557v3 fatcat:dmnyzjezxbba7nvdnlhhgxsyum

Smartphone Speech Testing for Symptom Assessment in Rapid Eye Movement Sleep Behavior Disorder and Parkinson's Disease

Siddharth Arora, Christine Lo, Michele Hu, Athanasios Tsanas
2021 IEEE Access  
Speech impairment in Parkinson's Disease (PD) has been extensively studied. Our understanding of speech in people who are at an increased risk of developing PD is, however, rather limited.  ...  We used acoustic signal analysis and machine learning, employing 337 features that quantify different properties of speech impairment.  ...  ACKNOWLEDGMENT The authors would like to thank the participants of this study for their commitment and time, that made this research possible.  ... 
doi:10.1109/access.2021.3057715 fatcat:ngiz44nmojcg3pudf4pnemxtge

Spectrally specific temporal analyses of spike-train responses to complex sounds: A unifying framework

Satyabrata Parida, Hari Bharadwaj, Michael G Heinz
2021 PLoS Computational Biology  
This unifying framework significantly expands the potential of preclinical animal models to advance our understanding of the physiological correlates of perceptual deficits in real-world listening following  ...  Here, we describe a unifying framework to study temporal coding of complex sounds that allows spike-train and evoked-response data to be analyzed and compared using the same advanced signal-processing  ...  We also thank François Deloche, Hannah Ginsberg, Caitlin Heffner, and Vibha Viswanathan for their valuable feedback on an earlier version of this manuscript.  ... 
doi:10.1371/journal.pcbi.1008155 pmid:33617548 pmcid:PMC7932515 fatcat:6ftbdffeufeeba6nhditzgg2ca

A Survey on Biometric Authentication: Toward Secure and Privacy-Preserving Identification

Zhang Rui, Zheng Yan
2019 IEEE Access  
The literature still lacks a thorough review on the recent advances of biometric authentication for the purpose of secure and privacy-preserving identification.  ...  Based on our survey, we figure out a number of open research issues and further specify a number of significant research directions that are worth special efforts in future research.  ...  [15] proposed a unified framework based on random projections and sparse representations. Its algorithm can deal with common distortion in iris image collection.  ... 
doi:10.1109/access.2018.2889996 fatcat:t4w4tsvk7zgsvklapjeagdrzne

Optimal set of EEG features for emotional state classification and trajectory visualization in Parkinson's disease

R. Yuvaraj, M. Murugappan, Norlinah Mohamed Ibrahim, Kenneth Sundaraj, Mohd Iqbal Omar, Khairiyah Mohamad, R. Palaniappan
2014 International Journal of Psychophysiology  
This provides a promising way of implementing visualization of patient's emotional state in real time and leads to a practical system for noninvasive assessment of the emotional impairments associated  ...  To classify the EEG-based emotional states and visualize the changes of emotional states over time, this paper compares four kinds of EEG features for emotional state classification and proposes an approach  ...  Shahrul Azmin for their assistance with recruitment of PD participants. Also we would like to thank all of the individuals who participated in this study. Emotional state classification in PD  ... 
doi:10.1016/j.ijpsycho.2014.07.014 pmid:25109433 fatcat:ofzmzx5cdfbuxgbh5oconsrj2e
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