Speech recognition using deep neural networks: A systematic review
Over the past decades, a tremendous amount of research has been done on the use of
machine learning for speech processing applications, especially speech recognition …
machine learning for speech processing applications, especially speech recognition …
Ensemble deep learning in speech signal tasks: a review
Abstract Machine learning methods are extensively used for processing and analysing
speech signals by virtue of their performance gains over multiple domains. Deep learning …
speech signals by virtue of their performance gains over multiple domains. Deep learning …
A survey of voice pathology surveillance systems based on internet of things and machine learning algorithms
The incorporation of the cloud technology with the Internet of Things (IoT) is significant in
order to obtain better performance for a seamless, continuous, and ubiquitous framework …
order to obtain better performance for a seamless, continuous, and ubiquitous framework …
[PDF][PDF] End-To-End Audio Replay Attack Detection Using Deep Convolutional Networks with Attention.
With automatic speaker verification (ASV) systems becoming increasingly popular, the
development of robust countermeasures against spoofing is needed. Replay attacks pose a …
development of robust countermeasures against spoofing is needed. Replay attacks pose a …
Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson's Disease
L Moro-Velazquez, JA Gómez-García… - Applied Soft …, 2018 - Elsevier
The diagnosis of Parkinson's Disease is a challenging task which might be supported by
new tools to objectively evaluate the presence of deviations in patient's motor capabilities …
new tools to objectively evaluate the presence of deviations in patient's motor capabilities …
On the design of automatic voice condition analysis systems. Part I: Review of concepts and an insight to the state of the art
JA Gómez-García, L Moro-Velázquez… - … Signal Processing and …, 2019 - Elsevier
This is the first of a two-part series devoted to review the current state of the art of automatic
voice condition analysis systems. The goal of this paper is to provide to the scientific …
voice condition analysis systems. The goal of this paper is to provide to the scientific …
An incremental method combining density clustering and support vector machines for voice pathology detection
R Amami, A Smiti - Computers & Electrical Engineering, 2017 - Elsevier
Abstract Machine learning techniques are a valuable tool for discriminative classification.
They have been applied to a diverse range of applications in speech processing, such as …
They have been applied to a diverse range of applications in speech processing, such as …
A lightly supervised approach to detect stuttering in children's speech
S Alharbi, M Hasan, AJH Simons… - … of Interspeech 2018, 2018 - eprints.whiterose.ac.uk
© 2018 International Speech Communication Association. All rights reserved. In speech
pathology, new assistive technologies using ASR and machine learning approaches are …
pathology, new assistive technologies using ASR and machine learning approaches are …
Automatic detection of laryngeal pathologies in records of sustained vowels by means of mel-frequency cepstral coefficient parameters and differentiation of patients …
Mel-frequency cepstral coefficients (MFCC) have traditionally been used in speaker
identification applications. Their use has been extended to speech quality assessment for …
identification applications. Their use has been extended to speech quality assessment for …
Voice disguise in automatic speaker recognition
M Farrús - ACM Computing Surveys (CSUR), 2018 - dl.acm.org
Humans are able to identify other people's voices even in voice disguise conditions.
However, we are not immune to all voice changes when trying to identify people from voice …
However, we are not immune to all voice changes when trying to identify people from voice …