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A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning [article]

Sameer Khurana, Antoine Laurent, Wei-Ning Hsu, Jan Chorowski, Adrian Lancucki, Ricard Marxer, James Glass
<span title="2020-09-08">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this work, we propose Convolutional Deep Markov Model (ConvDMM), a Gaussian state-space model with non-linear emission and transition functions modelled by deep neural networks.  ...  This unsupervised model is trained using black box variational inference. A deep convolutional neural network is used as an inference network for structured variational approximation.  ...  We propose Convolutional Deep Markov Model (Con-vDMM), a Gaussian state-space model with non-linear emission and transition functions parametrized by deep neural networks and a Deep Convolutional inference  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.02547v2">arXiv:2006.02547v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6x67rbwgqraprmovzje4nkny2i">fatcat:6x67rbwgqraprmovzje4nkny2i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200918131350/https://arxiv.org/pdf/2006.02547v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2006.02547v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning

Sameer Khurana, Antoine Laurent, Wei-Ning Hsu, Jan Chorowski, Adrian Lancucki, Ricard Marxer, James Glass
<span title="2020-10-25">2020</span> <i title="ISCA"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/trpytsxgozamtbp7emuvz2ypra" style="color: black;">Interspeech 2020</a> </i> &nbsp;
In this work, we propose Convolutional Deep Markov Model (ConvDMM), a Gaussian state-space model with non-linear emission and transition functions modelled by deep neural networks.  ...  This unsupervised model is trained using black box variational inference. A deep convolutional neural network is used as an inference network for structured variational approximation.  ...  We propose Convolutional Deep Markov Model (Con-vDMM), a Gaussian state-space model with non-linear emission and transition functions parametrized by deep neural networks and a Deep Convolutional inference  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21437/interspeech.2020-3084">doi:10.21437/interspeech.2020-3084</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/interspeech/KhuranaLHCLMG20.html">dblp:conf/interspeech/KhuranaLHCLMG20</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2resntl7wzhoxi2elxcfgqkjsq">fatcat:2resntl7wzhoxi2elxcfgqkjsq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201213231146/https://www.isca-speech.org/archive/Interspeech_2020/pdfs/3084.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/25/47/254787d62db0d49ae337cb4be9ad72a76a3270bc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.21437/interspeech.2020-3084"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Deep Learning of Representations [chapter]

Yoshua Bengio, Aaron Courville
<span title="">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ofs2kbxnpzeeto5wtnrfgobke4" style="color: black;">Intelligent Systems Reference Library</a> </i> &nbsp;
Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In L. Bottou and M.  ...  Unsupervised feature learning for audio classification using convolutional deep belief networks. In Y. Bengio, D. Schuurmans, C. Williams, J. Lafferty, and A.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-36657-4_1">doi:10.1007/978-3-642-36657-4_1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/itdt75pd6bavve25ta4uxruxs4">fatcat:itdt75pd6bavve25ta4uxruxs4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150814023754/http://www.iro.umontreal.ca/~bengioy/talks/aaai2013-tutorial-refs.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b1/ae/b1ae81e35eb0778ecf13ddea8e6fbc8c60507911.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-36657-4_1"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Towards an Efficient Voice Identification Using Wav2Vec2.0 and HuBERT Based on the Quran Reciters Dataset [article]

Aly Moustafa, Salah A. Aly
<span title="2021-11-11">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, we develop a deep learning constructed model for Arabic speakers identification by using Wav2Vec2.0 and HuBERT audio representation learning tools.  ...  The end-to-end Wav2Vec2.0 paradigm acquires contextualized speech representations learnings by randomly masking a set of feature vectors, and then applies a transformer neural network.  ...  ACKNOWLEDGEMENT This research is partially funded by a grant from the academy of scientific research and technology (ASRT), 2020-2021, research grant number 6547.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2111.06331v1">arXiv:2111.06331v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/y2xayleywvagfogradf6l5mep4">fatcat:y2xayleywvagfogradf6l5mep4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211122063047/https://arxiv.org/pdf/2111.06331v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6f/83/6f83ee4863de38607b99b541098e2157c4d21da3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2111.06331v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

A review of unsupervised feature learning and deep learning for time-series modeling

Martin Längkvist, Lars Karlsson, Amy Loutfi
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6r4znskbk5h2ngu345slqsm6eu" style="color: black;">Pattern Recognition Letters</a> </i> &nbsp;
This paper gives a review of the recent developments in deep learning and unsupervised feature learning for time-series problems.  ...  While these techniques have shown promise for modeling static data, such as computer vision, applying them to time-series data is gaining increasing attention.  ...  Unsupervised feature learning and deep learning This section presents both models that are used for unsupervised feature learning and models and techniques that are used for modeling temporal relations  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patrec.2014.01.008">doi:10.1016/j.patrec.2014.01.008</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zhc3pdwxhbhztnjqyrwpuofp6q">fatcat:zhc3pdwxhbhztnjqyrwpuofp6q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20150820001719/http://www.diva-portal.org:80/smash/get/diva2:710518/FULLTEXT02" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e7/18/e718fae69462e8008a1eb4de0d63c4bed2fec88a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.patrec.2014.01.008"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Deep Machine Learning and Neural Networks: An Overview

Chandrahas Mishra, Dharmendra Lal Gupta
<span title="2016-11-30">2016</span> <i title="Science and Engineering Research Support Society"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rebsgv7gbjechhypg6np633rcu" style="color: black;">International Journal of Hybrid Information Technology</a> </i> &nbsp;
Deep learning refers to a class of ML techniques, where numerous layers of data processing stages in various leveled architectures are exploited for unsupervised feature learning and for pattern classification  ...  Deep learning is a technique of machine learning in artificial intelligence area.  ...  procedures to consequently learn various leveled representations in deep models for classification.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijhit.2016.9.11.34">doi:10.14257/ijhit.2016.9.11.34</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tvbfxbm5pnea5bjsjy5w7t3jem">fatcat:tvbfxbm5pnea5bjsjy5w7t3jem</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180603085133/http://www.sersc.org/journals/IJHIT/vol9_no11_2016/34.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bd/e6/bde69b585c8514ba94cd74220bc0356fe416e14f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.14257/ijhit.2016.9.11.34"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Deep Reinforcement Learning: An Overview [chapter]

Seyed Sajad Mousavi, Michael Schukat, Enda Howley
<span title="2017-08-23">2017</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/f62eqyiywnayfk3dg62ohcylbm" style="color: black;">Lecture Notes in Networks and Systems</a> </i> &nbsp;
Recent research has also been shown that deep learning techniques can be combined with reinforcement learning methods to learn useful representations for the problems with high dimensional raw data input  ...  In recent years, a specific machine learning method called deep learning has gained huge attraction, as it has obtained astonishing results in broad applications such as pattern recognition, speech recognition  ...  combination of deep unsupervised learning models with RL.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-56991-8_32">doi:10.1007/978-3-319-56991-8_32</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/hyphl437obfqpfkphppc5bku3y">fatcat:hyphl437obfqpfkphppc5bku3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190221232651/http://pdfs.semanticscholar.org/3020/64af13abe75a55a748198f42c9d652919a1f.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/30/20/302064af13abe75a55a748198f42c9d652919a1f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-56991-8_32"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Deep Representation Learning in Speech Processing: Challenges, Recent Advances, and Future Trends [article]

Siddique Latif, Rajib Rana, Sara Khalifa, Raja Jurdak, Junaid Qadir, Björn W. Schuller
<span title="2021-09-24">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Recent reviews in speech have been conducted for ASR, SR, and SER, however, none of these has focused on the representation learning from speech -- a gap that our survey aims to bridge.  ...  This has motivated the adoption of a recent trend in speech community towards utilisation of representation learning techniques, which can learn an intermediate representation of the input signal automatically  ...  Brief History on Deep Learning (DL) in Speech Technology For decades, the Gaussian Mixture Model (GMM) and Hidden Markov Model (HMM) based models (GMM-HMM) ruled the speech technology due to their many  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2001.00378v2">arXiv:2001.00378v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ysvljxylwnajrbowd3kfc7l6ve">fatcat:ysvljxylwnajrbowd3kfc7l6ve</a> </span>
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Dual Exclusive Attentive Transfer for Unsupervised Deep Convolutional Domain Adaptation in Speech Emotion Recognition

Elias Nii Noi Ocquaye, Qirong Mao, Heping Song, Guopeng Xu, Yanfei Xue
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Addressing this challenge via a domain adaptation method, we propose a dual exclusive attentive transfer (DEAT) for deep convolutional neural network architecture based on unsupervised domain adaptation  ...  INDEX TERMS Attention transfer, correlation alignment, convolutional neural network, speech emotion recognition, unsupervised domain adaptation.  ...  We propose Dual Exclusive Attentive Transfer (DEAT) model for unsupervised DA using deep convolutional neural network.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2924597">doi:10.1109/access.2019.2924597</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eystcdogzba7ng2prr32kwxr2m">fatcat:eystcdogzba7ng2prr32kwxr2m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429162005/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08744334.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d9/3d/d93d2fe0ab4e8c2812f91de87a5d36d5ce1f7ef1.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2924597"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Bio-inspired Multi-layer Spiking Neural Network Extracts Discriminative Features from Speech Signals [chapter]

Amirhossein Tavanaei, Anthony Maida
<span title="">2017</span> <i title="Springer International Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
To assess the discriminative power of the learned features, they are used in a hidden Markov model (HMM) for spoken digit recognition.  ...  This paper develops a bio-inspired SNN that uses unsupervised learning to extract discriminative features from speech signals, which can subsequently be used in a classifier.  ...  The initial promising results obtained by unsupervised learning in this model offer promise of scaling to larger problems, such as developing a deep spiking network for the large vocabulary speech recognition  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-70136-3_95">doi:10.1007/978-3-319-70136-3_95</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yknftatjgnh7fhrhgtc6eu74yq">fatcat:yknftatjgnh7fhrhgtc6eu74yq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200911164842/https://arxiv.org/pdf/1706.03170v1.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/4f/05/4f058fc172ebc80cdf33fef115ed9d850349a664.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-319-70136-3_95"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization [article]

Zhiguang Wang, Wei Song, Lu Liu, Fan Zhang, Junxiao Xue, Yangdong Ye, Ming Fan, Mingliang Xu
<span title="2016-11-26">2016</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We propose a new model based on the deconvolutional networks and SAX discretization to learn the representation for multivariate time series.  ...  Deconvolutional networks fully exploit the advantage the powerful expressiveness of deep neural networks in the manner of unsupervised learning.  ...  Most exciting advance comes from the exploration of unsupervised learning algorithms for generative models, such as Deep Belief Networks (DBN) and Denoised Auto-encoders (DA) [16, 17] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1610.07258v3">arXiv:1610.07258v3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/zbtu54kqknguvaezchem7q6hia">fatcat:zbtu54kqknguvaezchem7q6hia</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200906015725/https://arxiv.org/pdf/1610.07258v3.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b3/fb/b3fbd2e9d69b8d3e94a776f1703cb37a4f2177b8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1610.07258v3" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Speech Recognition using Deep Neural Network Neural (DNN) and Deep Belief Network (DBN)

Prof. Kirti Rajadnya
<span title="2020-05-31">2020</span> <i title="International Journal for Research in Applied Science and Engineering Technology (IJRASET)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hsp44774azcezeyiq4kuzpfh5a" style="color: black;">International Journal for Research in Applied Science and Engineering Technology</a> </i> &nbsp;
Deep learning also known as representation learning or sometimes referred as unsupervised feature learning, is a subset of machine learning.  ...  Deep learning is becoming a conventional technology for speech recognition and has efficiently replaced Gaussian mixtures for speech recognition on a global scale.  ...  DNN-HMM alongside an unsupervised pre-training method to train a Deep Belief Network, which has the strong ability of feature learning provides a better recognition result.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2020.5359">doi:10.22214/ijraset.2020.5359</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/am5bd67spzaovgmrlosrftjtcm">fatcat:am5bd67spzaovgmrlosrftjtcm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200528083717/http://ijraset.com/fileserve.php?FID=28901" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.22214/ijraset.2020.5359"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Energy-Based Models in Document Recognition and Computer Vision

Y. LeCun, S. Chopra, M. Ranzato, F.-J. Huang
<span title="">2007</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/xtwegnbfind35bohrbjjlwcv7i" style="color: black;">Proceedings of the International Conference on Document Analysis and Recognition</a> </i> &nbsp;
We show that using unsupervised learning to initialize the layers of a deep network dramatically reduces the required number of training samples, particularly for such tasks as the recognition of everyday  ...  We first consider "traditional" methods for deep learning, such as convolutional networks and backpropagation, and show that, although they produce very low error rates for handwriting and object recognition  ...  In a more recent work, a method was proposed to learn a deep hierarchy of increasingly invariant features, by including the "feature pooling" layer of a convolutional net into the unsupervised module  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icdar.2007.4378728">doi:10.1109/icdar.2007.4378728</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icdar/LeCunCRH07.html">dblp:conf/icdar/LeCunCRH07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yoejktkyifc3je2bt7n6sbypme">fatcat:yoejktkyifc3je2bt7n6sbypme</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810085417/http://yann.lecun.com/exdb//publis/pdf/lecun-icdar-keynote-07.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c0/9c/c09c49d92d10a84e6efdbaf67d979bab2c22be3e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icdar.2007.4378728"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Survey on Neural Network Architectures with Deep Learning

Smys S., Joy Iong Zong Chen, Subarna Shakya
<span title="2020-07-30">2020</span> <i title="Inventive Research Organization"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6igvoisvxncxta4zp6e7h5joma" style="color: black;">Journal of Soft Computing Paradigm</a> </i> &nbsp;
Also, this research work analyses recent trends in deep learning through various literatures to explore the present evolution in deep learning models.  ...  In particular deep learning is one of the cost efficient, effective supervised learning model, which can be applied to various complicated issues.  ...  Based on the emission probabilities in hidden Markov models, a discriminative learning neural network model tandem is evolved.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36548/jscp.2020.3.007">doi:10.36548/jscp.2020.3.007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/saxneqmonvdy7iv6qzkpkoii3y">fatcat:saxneqmonvdy7iv6qzkpkoii3y</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210228204940/https://www.irojournals.com/jscp/V2/I3/06.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/40/3e/403efd62927c9f6ed69b12aeff287623c2da2c36.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.36548/jscp.2020.3.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

2019 Index IEEE/ACM Transactions on Audio, Speech, and Language Processing Vol. 27

<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rut5unc4enborm7fhpkwgeza7m" style="color: black;">IEEE/ACM Transactions on Audio Speech and Language Processing</a> </i> &nbsp;
., +, TASLP Jan. 2019 140-153 Unsupervised Speech Representation Learning Using WaveNet Autoencoders.  ...  ., +, TASLP Jan. 2019 212-224 Unsupervised Speech Representation Learning Using WaveNet Autoencoders.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/taslp.2020.2971902">doi:10.1109/taslp.2020.2971902</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/j66uwjyqlfbmtgda6zhzlswpva">fatcat:j66uwjyqlfbmtgda6zhzlswpva</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201108185639/https://ieeexplore.ieee.org/ielx7/6570655/8817316/09007554.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3e/88/3e8847365bd9b10c332e7659e4d8c443b978b6ef.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/taslp.2020.2971902"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>
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