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Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels
[article]
2020
arXiv
pre-print
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MGLM marginalizes over all possible factorizations within and across all channels. ...
In this work, we present the Multichannel Generative Language Model (MGLM). MGLM is a generative joint distribution model over channels. ...
Acknowledgement We give thanks to Mohammad Norouzi, Lala Li, Sara Sabour, Geoffrey Hinton, Silviu Pitis, and the Google Brain team for useful discussions and feedbacks. ...
arXiv:2010.04438v1
fatcat:53jndthyq5ev3itqvhaw6456qy
Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels
2020
Findings of the Association for Computational Linguistics: EMNLP 2020
unpublished
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MGLM marginalizes over all possible factorizations within and across all channels. ...
In this work, we present the Multichannel Generative Language Model (MGLM). MGLM is a generative joint distribution model over channels. ...
Acknowledgement We give thanks to Mohammad Norouzi, Lala Li, Sara Sabour, Geoffrey Hinton, Silviu Pitis, and the Google Brain team for useful discussions and feedbacks. ...
doi:10.18653/v1/2020.findings-emnlp.376
fatcat:jxf6w5oxmrfilcfrrj3z4vt3ia
A Metaheuristic Autoencoder Deep Learning Model for Intrusion Detector System
2022
Mathematical Problems in Engineering
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Unaided multichannel characteristic learning and supervised cross-channel characteristic dependency are used to develop an effective intrusion detection model. ...
Next, a one-dimensional convolution neural network (CNN) learns probable relationships across channels to better discriminate between ordinary and attack traffic. ...
the feature combination information across channels. ...
doi:10.1155/2022/3859155
fatcat:ku6u6x7vnramjbzu2v5asjysg4
Modeling Local Dependence in Natural Language with Multi-channel Recurrent Neural Networks
[article]
2018
arXiv
pre-print
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To verify the effectiveness of MC-RNN, we conduct extensive experiments on typical natural language processing tasks, including neural machine translation, abstractive summarization, and language modeling ...
Recurrent Neural Networks (RNNs) have been widely used in processing natural language tasks and achieve huge success. Traditional RNNs usually treat each token in a sentence uniformly and equally. ...
the Central Universities and SAFEA: Overseas Young Talents in Cultural and Educational Sector. ...
arXiv:1811.05121v1
fatcat:zdxqssw36rejrbc6zlpm5wwt2a
Channels in the Mirror: An Alignable Model for Assessing Customer Satisfaction in Concurrent Channel Systems
2019
Figshare
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The resulting 5C model is superior to existing models in that it enables the unified capture of both off-line and online satisfaction, allowing a meaningful comparison across formats. ...
The 5C model also supports within-channel decisions by revealing the impact of the five facets on overall satisfaction with each format. ...
Acknowledgment The authors thank Editor Mary Jo Bitner, former Editor Kay Lemon, and three anonymous reviewers as well as Deva Rangarajan and Niels Schillewaert for helpful comments and suggestions for ...
doi:10.6084/m9.figshare.7622069
fatcat:qgreujnq4ndb5fkfbxemfhx4va
Modeling Local Dependence in Natural Language with Multi-Channel Recurrent Neural Networks
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
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To verify the effectiveness of MC-RNN, we conduct extensive experiments on typical natural language processing tasks, including neural machine translation, abstractive summarization, and language modeling ...
Recurrent Neural Networks (RNNs) have been widely used in processing natural language tasks and achieve huge success. Traditional RNNs usually treat each token in a sentence uniformly and equally. ...
the Central Universities and SAFEA: Overseas Young Talents in Cultural and Educational Sector. ...
doi:10.1609/aaai.v33i01.33015525
fatcat:qvfsongkmvdv7otx3n5rgquevu
Interactive dialogue model: a design technique for multichannel applications
2006
IEEE transactions on multimedia
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of consistency across the different channels and the perception that they are "different applications"). ...
This paper presents an interactive dialogue model (IDM), a novel design model specifically tailored for multichannel applications. ...
Different factors are being implied here. 1) It must be easy to teach the design methodology (and the design model) to anyone (from students to practitioners invest for learning new methodologies; one ...
doi:10.1109/tmm.2006.870733
fatcat:qk36zysvwzfbvh6egjytxkngze
Raw Multichannel Processing Using Deep Neural Networks
[chapter]
2017
New Era for Robust Speech Recognition
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compared to a single channel waveform model. ...
Multichannel ASR systems commonly separate speech enhancement, including localization, beamforming and postfiltering, from acoustic modeling. ...
Even though the time and frequency models all learn different spatial filters, they all seem to have similar WERs. ...
doi:10.1007/978-3-319-64680-0_5
fatcat:22k7btluzvalnf7sbepu5w5pae
Extension of hidden markov model for recognizing large vocabulary of sign language
[article]
2013
arXiv
pre-print
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Unlike speech recognition, Frensh sign language (FSL) events occur both sequentially and simultaneously. Thus, the computational processing of FSL is too complex than the spoken languages. ...
In this work, we are dealing with sign language recognition, in particular of French Sign Language (FSL). ...
A multi-dimensional HMM is capable to deal with multichannel signs which are general cases of sign language recognition. ...
arXiv:1304.3265v1
fatcat:wp32trwimrfx5b2a65okkch47a
Evaluating the impact of AI on insurance: The four emerging AI- and data-driven business models
2019
Emerald Open Research
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In the third model the insurer adapts their model to fully utilize AI and seek new sources of data and customers. ...
In the second model the insurer keeps the same model and value chain but uses AI to improve effectiveness. ...
The constructs were used for within case analysis and across case analysis. ...
doi:10.35241/emeraldopenres.13249.1
fatcat:ododxeelsbfsfammzy4rdglcim
MIC: Model-agnostic Integrated Cross-channel Recommenders
[article]
2022
arXiv
pre-print
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Specifically, MIC robustly models correlation within user-item, user-user, and item-item from latent interactions in a universal schema. ...
In this paper, we propose a model-agnostic integrated cross-channel (MIC) approach for the large-scale recommendation, which maximally leverages the inherent multi-channel mutual information to enhance ...
Specifically, MIC models correlation across user-item (U2I), user-user (U2U), and item-item (I2I) channels via intra and inter cross-channel contrastive modules. ...
arXiv:2110.11570v2
fatcat:i52iepprnzdxtkc5sj4ja23jcy
Recent Progresses in Deep Learning based Acoustic Models (Updated)
[article]
2018
arXiv
pre-print
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We also cover modeling techniques that lead to more efficient decoding and discuss possible future directions in acoustic model research. ...
In this paper, we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed techniques. ...
It is obvious that each output pixel is a weighted sum of all pixels across all channels in an input patch. ...
arXiv:1804.09298v2
fatcat:yfxzxu6qanbndcnmt3loikqeym
Recent progresses in deep learning based acoustic models
2017
IEEE/CAA Journal of Automatica Sinica
Preserved Fulltext
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We also cover modeling techniques that lead to more efficient decoding and discuss possible future directions in acoustic model research. ...
In this paper, we summarize recent progresses made in deep learning based acoustic models and the motivation and insights behind the surveyed techniques. ...
It is obvious that each output pixel is a weighted sum of all pixels across all channels in an input patch. ...
doi:10.1109/jas.2017.7510508
fatcat:zcffvbg75bhllcekqghkmwidsy
Extension of Hidden Markov Model for Recognizing Large Vocabulary of Sign Language
2013
International Journal of Artificial Intelligence & Applications
Preserved Fulltext
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The file type is application/pdf.
Unlike speech recognition, Frensh sign language (FSL) events occur both sequentially and simultaneously. Thus, the computational processing of FSL is too complex than the spoken languages. ...
In this work, we are dealing with sign language recognition, in particular of French Sign Language (FSL). ...
A multi-dimensional HMM is capable to deal with multichannel signs which are general cases of sign language recognition. ...
doi:10.5121/ijaia.2013.4203
fatcat:fe3foqvrdvazld375bixarzlbe
A Deep Neural Model Of Emotion Appraisal
[article]
2018
arXiv
pre-print
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We deployed the model in an iCub robot and evaluated the capability of the robot to learn and describe the affective behavior of different persons based on observation. ...
In this paper, we propose a deep neural model which is designed in the light of different aspects of developmental learning of emotional concepts to provide an integrated solution for internal and external ...
The modulation factor is defined as γ and it has a value within the interval of [0, 1]. ...
arXiv:1808.00252v1
fatcat:zp3qgbqafrdofaxbeykss6g7oy
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