A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
Speaker Attribution with Voice Profiles by Graph-Based Semi-Supervised Learning
2020
Interspeech 2020
Preserved Fulltext
Other Versions
In this paper, we propose to solve the speaker attribution problem by using graph-based semi-supervised learning methods. ...
Speaker attribution then becomes a semi-supervised learning problem on graphs, on which two graph-based methods are applied: label propagation (LP) and graph neural networks (GNNs). ...
Conclusion In this work, we applied graph-based semi-supervised learning methods for the speaker attribution task with speaker voice profiles. ...
doi:10.21437/interspeech.2020-1950
dblp:conf/interspeech/WangXWRRB20
fatcat:v24rgjdqnbfpjgm5lhgw2u2gle
Graph-based Label Propagation for Semi-Supervised Speaker Identification
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
We propose a graph-based semi-supervised learning approach for speaker identification in the household scenario, to leverage the unlabeled speech samples. ...
well as their semi-supervised variants based on pseudo-labels. ...
Semi-supervised learning (SSL) is a technique to reduce the dependency on annotations by learning from unlabeled, as well as labeled, data. ...
arXiv:2106.08207v1
fatcat:5kjp7bohtfbp3lqgn3wd2emmwe
Three recent trends in Paralinguistics on the way to omniscient machine intelligence
2018
Journal on Multimodal User Interfaces
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
While this is not reached at the time for many tasks such as speaker emotion recognition, deep learning-often described to lead to significant improvements-in combination with sufficient learning data, ...
Smallworld modelling in combination with unsupervised learning help to rapidly identify potential target data of interest. ...
Cooperative learning: human + machine Aiming to reduce human labelling effort has long since led to the idea of self-learning by machines such as by unsupervised, semi-supervised, or active learning. ...
doi:10.1007/s12193-018-0270-6
fatcat:cqlvp4ozmbe6zponscyplel45i
Empowering Things with Intelligence: A Survey of the Progress, Challenges, and Opportunities in Artificial Intelligence of Things
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Then, we present progress in AI research for IoT from four perspectives: perceiving, learning, reasoning, and behaving. ...
Artificial intelligence (AI), especially deep learning, is now a proven success in various areas including computer vision, speech recognition, and natural language processing. ...
TIMIT APCSC
https://catalog.ldc.upenn.edu/LDC93S1
630 speakers
Text, ID
Common Voice https://commonvoice.mozilla.org/en/datasets
61,528 voices
ID, Attributes
widely used calibration method is proposed ...
arXiv:2011.08612v1
fatcat:dflut2wdrjb4xojll34c7daol4
A subspace co-training framework for multi-view clustering
2014
Pattern Recognition Letters
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The new algorithm is flexible and can be readily adapted to use different distance measures, semi-supervised learning, and non-linear problems. ...
We propose a new algorithm which learns discriminative subspaces in an unsupervised fashion based upon the assumption that a reliable clustering should assign same-class samples to the same cluster in ...
Co-training Co-training (Blum and Mitchell, 1998) is one of the most acclaimed approaches to semi-supervised learning. ...
doi:10.1016/j.patrec.2013.12.003
fatcat:2guqz674afbsxk5kkrt346tvy4
A Review on Voice-based Interface for Human-Robot Interaction
2020
Iraqi Journal for Electrical And Electronic Engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
With the recent developments of technology and the advances in artificial intelligence and machine learning techniques, it has become possible for the robot to understand and respond to voice as part of ...
The voice-based interface robot can recognize the speech information from humans so that it will be able to interact more naturally with its human counterpart in different environments. ...
ARI is an autonomous or semi-autonomous robot where the robot decision is made based on the awareness of environmental information from the user, where this information may include user profile, user emotions ...
doi:10.37917/ijeee.16.2.10
fatcat:crz5ieseo5g5nmcllbpm5oz22e
Motivations, Methods and Metrics of Misinformation Detection: An NLP Perspective
2020
Natural Language Processing Research
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Advantages and disadvantages of the key techniques are also addressed with focuses on content-based analysis and predicative modeling. ...
This paper discusses the main issues of misinformation and its detection with a comprehensive review on representative works in terms of detection methods, feature representations, evaluation metrics and ...
[54] propose a semi-supervised method for content-based detection of misinformation via tensor embeddings. ...
doi:10.2991/nlpr.d.200522.001
fatcat:vwwspvaexbga3kn5mxtdo6ke6u
Improving Speech Emotion Recognition Using Graph Attentive Bi-Directional Gated Recurrent Unit Network
2020
Interspeech 2020
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Our proposed GA-GRU combines both long-range time-series based modeling of speech and further integrates complex saliency using a graph structure. ...
In this work, we propose a framework in imposing a graph attention mechanism on gated recurrent unit network (GA-GRU) to improve utterance-based speech emotion recognition (SER). ...
Attention and Graph Analysis We provide an analysis on the learned graph-based attention weights. ...
doi:10.21437/interspeech.2020-1733
dblp:conf/interspeech/SuCLL20
fatcat:5soj4gpfr5cnpeglq63itm23nu
Audio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 accepted arXiv:2101.09725v2 fatcat:4n3gqlbw4nbpfag5ynmmhp6psy
Amidst the classically used biometrics, voice and face attributes are the most propitious for prevalent applications in day-to-day life because they are easy to obtain through restrained and user-friendly ...
For many years, acoustic information alone has been a great success in automatic speaker verification applications. ...
The MSDA is inspired by a multi-view semi-supervised learning method called co-training [19] . ...
arXiv:2101.09725v1
fatcat:huejyfaeojhzddlckqt5nfivlq
Audio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Amidst the classically used biometrics, voice and face attributes are the most propitious for prevalent applications in day-to-day life because they are easy to obtain through restrained and user-friendly ...
For many years, acoustic information alone has been a great success in automatic speaker verification applications. ...
The MSDA is inspired by a multi-view semi-supervised learning method called co-training [19] . ...
doi:10.1109/access.2021.3063031
fatcat:q6emam55frhlzp53t7lxb4qz3e
CUSTOMER SEGMENTATION AND CLASSIFICATION FROM BLOGS BY USING DATA MINING: AN EXAMPLE OF VOIP PHONE
2009
Cybernetics and systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Then, we can use supervised learning tools to extract knowledge. ...
(SOM) -Sparsity analysis Step 5: Supervised learning Back-Propagation Neural Network (BPN), C4.5, and (SVM) In step 1, blog mining users need to define a set of keywords to be the variables (attributes ...
doi:10.1080/01969720903152593
fatcat:4r5jgv2vgzaebbq2wa4bw7qz3i
CRF-Based Context Modeling for Person Identification in Broadcast Videos
2016
Frontiers in ICT
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
They choose a learning setting which takes into account 111 the label ambiguities, for example: multiple instance learning (Wohlhart et al. (2011)) and semi-supervised 112 strategies (Bauml et al. (2013 ...
2 We are investigating the problem of speaker and face identification in broadcast videos. 3 Identification is performed by associating automatically extracted names from overlaid texts 4 with speaker ...
it would be interesting to increase the recall of the face detector, for instance, by adding a profile view 498 detector. ...
doi:10.3389/fict.2016.00009
fatcat:emrygzd3uffxtfvu2unctmsw54
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Semi-supervised Deep Learning Techniques for Spectrum Reconstruction Hong, Hanbin; Bao, Wentao; Hong, Yuan; Kong, Yu 1187 Privacy Attributes-Aware Message Passing Neural Network for Visual Privacy Attributes ...
; Awate, Suyash
1551
Generative Deep-Neural-Network Mixture Modeling with Semi-
Supervised MinMax+EM Learning
DAY 3 -Jan 14, 2021
Sahoo, Saswata; Chakraborty,
Souradip
1559
Graph Spectral Feature ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
Deep Spoken Keyword Spotting: An Overview
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Welling, “Semi-supervised classification with graph
[111] H. Muckenhirn, M. Magimai.-Doss, and S. ...
Tami, “An overview of deep semi-
supervised learning,” arXiv:2006.05278v2, 2020.
[260] S. Sigtia, E. Marchi, S. Kajarekar, D. Naik, and J. ...
doi:10.1109/access.2021.3139508
fatcat:i4pfpfxcpretlkbefp7owtxcti
A Survey on Natural Language Processing for Fake News Detection
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Based on our insights, we outline promising research directions, including more fine-grained, detailed, fair, and practical detection models. ...
Machine Learning Models As mentioned in Section 3., the majority of existing research uses supervised methods while semi-supervised or unsupervised methods are less commonly used. ...
Therefore, semi/weakly-supervised and unsupervised methods are proposed (Rubin and Vashchilko, 2012; Bhattacharjee et al., 2017) . ...
arXiv:1811.00770v2
fatcat:muo74knnsfehlmhcopqzivfo6q
« Previous
Showing results 1 — 15 out of 1,998 results