Md Akmal Haidar
Md Akmal Haidar
Senior Researcher, Huawei Technologies Canada
Verified email at huawei.com
Title
Cited by
Cited by
Year
Semi-supervised regression with generative adversarial networks
M Rezagholizadeh, MA Haidar, D Wu
US Patent App. 15/789,518, 2018
16*2018
Unsupervised language model adaptation using LDA-based mixture models and latent semantic marginals
MA Haidar, D O'Shaughnessy
Computer Speech and Language, 2015
152015
Topic n-gram count language model adaptation for speech recognition
MA Haidar, D O'Shaughnessy
Spoken Language Technology Workshop (SLT), 2012 IEEE, 165-169, 2012
152012
Textkd-gan: Text generation using knowledge distillation and generative adversarial networks
MA Haidar, M Rezagholizadeh
Canadian Conference on Artificial Intelligence, 107-118, 2019
122019
Unsupervised language model adaptation using n-gram weighting
MA Haidar, D O'Shaughnessy
Electrical and Computer Engineering (CCECE), 2011 24th Canadian Conference …, 2011
122011
Salsa-text: self attentive latent space based adversarial text generation
J Gagnon-Marchand, H Sadeghi, MA Haidar, M Rezagholizadeh
Canadian Conference on Artificial Intelligence, 119-131, 2019
102019
Novel Weighting Scheme for Unsupervised Language Model Adaptation Using Latent Dirichlet Allocation
MA Haidar, D O'Shaughnessy
Eleventh Annual Conference of the International Speech Communication …, 2010
102010
COMPARISON OF A BIGRAM PLSA AND A NOVEL CONTEXT-BASED PLSA LANGUAGE MODEL FOR SPEECH RECOGNITION
MA Haidar, D O’Shaughnessy
ICASSP 2013, 2013
72013
LDA-BASED LM ADAPTATION USING LATENT SEMANTIC MARGINALS AND MINIMUM DISCRIMINANT INFORMATION
MA Haidar, D O’Shaughnessy
EUSIPCO 2012, 2012
72012
UNSUPERVISED LANGUAGE MODEL ADAPTATION USING LATENT DIRICHLET ALLOCATION AND DYNAMIC MARGINALS
MA Haidar, D O’Shaughnessy
EUSIPCO 2011, 2011
52011
Latent code and text-based generative adversarial networks for soft-text generation
M Haidar, M Rezagholizadeh, A Do-Omri, A Rashid
arXiv preprint arXiv:1904.07293, 2019
42019
Self-training method and system for semi-supervised learning with generative adversarial networks
D Wu, MA Haidar, M Rezagholizadeh, A Do-Omri
US Patent App. 15/789,628, 2019
32019
Bilingual-gan: A step towards parallel text generation
A Rashid, A Do-Omri, M Haidar, Q Liu, M Rezagholizadeh
arXiv preprint arXiv:1904.04742, 2019
32019
LDA-BASED CONTEXT DEPENDENT RECURRENT NEURAL NETWORK LANGUAGE MODEL USING DOCUMENT-BASED TOPIC DISTRIBUTION OF WORDS
MA Haidar, M Kurimo
ICASSP, 2017
32017
PLSA ENHANCED WITH A LONG-DISTANCE BIGRAM LANGUAGE MODEL FOR SPEECH RECOGNITION
MA Haidar, D O'Shaughnessy
EUSIPCO 2013, 2013
32013
DOCUMENT-SPECIFIC CONTEXT PLSA LANGUAGE MODEL FOR SPEECH RECOGNITION
MA Haidar, D O'Shaughnessy
ICASSP, 2015
22015
Language Modeling for Speech Recognition Incorporating Probabilistic Topic Models
MA Haidar
PhD thesis, Université du Québec, 2014
22014
Novel Topic N-gram Count LM Incorporating Document-based Topic Distributions and N-gram Counts
MA Haidar, D O'Shaughnessy
EUSIPCO2014, 2014
22014
Fitting Long-range Information Using Interpolated Distanced N-grams and Cache Models into a Latent Dirichlet Language Model for Speech Recognition
MA Haidar, D O'Shaughnessy
INTERSPEECH 2013, 2013
22013
Latent Space and Text-Based Generative Adversarial Networks (LATEXT-GANs) for Text Generation
MA Haidar, M Rezagholizadeh
US Patent App. 16/175,373, 2020
12020
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