@inproceedings{iccit2020Arid,
title = {Sentiment Classification in Bangla Textual Content: A Comparative Study},
author = {Md. Arid Hasan and Jannatul Tajrin and Shammur Absar Chowdhury and Firoj Alam},
year  = {2020},
date = {2020-12-01},
booktitle = {23rd International Conference on Computer and Information Technology (ICCIT)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@misc{alam2020bangla,
title = {Bangla Text Classification using Transformers},
author = {Tanvirul Alam and Akib Khan and Firoj Alam},
year  = {2020},
date = {2020-01-01},
keywords = {},
pubstate = {published},
tppubtype = {misc}
}
@inproceedings{arid2019neural,
title = {Neural Machine Translation for Bangla-English Language Pair},
author = {Md. Arid Hasan and Firoj Alam and Shammur Absar Chowdhury and Naira Khan},
url = {https://www.researchgate.net/publication/338223294_Neural_Machine_Translation_for_the_Bangla-English_Language_Pair},
year  = {2019},
date = {2019-12-18},
booktitle = {2019 22nd International Conference of Computer and Information Technology (ICCIT)},
organization = {IEEE},
abstract = {Due to the rapid advancement of different neural network architectures, the task of automated translation from one language to another is now in a new era of Machine Translation (MT) research. In the last few years, Neural Machine Translation (NMT) architectures have proven to be successful for resource-rich languages, trained on a large dataset of translated sentences, with variations of NMT algorithms used to train the model. In this study, we explore different NMT algorithms-Bidirectional Long Short Term Memory (LSTM) and Transformer based NMT, to translate the Bangla to English language pair. For the experiments, we used different datasets and our experimental results outperform the existing performance by a large margin on different datasets. We also investigated the factors affecting the data quality and how they influence the performance of the models. It shows a promising research avenue to enhance NMT for the Bangla-English language pair.},
keywords = {Bangla-to-English, Bidirectional LSTM, Machine Translation, Neural Machine Translation, Transformer},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{arid2019MTb,
title = {Neural vs Statistical Machine Translation: Revisiting the Bangla-English Language Pair},
author = {Arid Hasan and Firoj Alam and Shammur Absar Chowdhury and Naira Khan},
url = {https://www.researchgate.net/publication/338223297_Neural_vs_Statistical_Machine_Translation_Revisiting_the_Bangla-English_Language_Pair},
year  = {2019},
date = {2019-01-01},
booktitle = {2nd International Conference on Bangla Speech and Language Processing (ICBSLP)},
abstract = {Machine translation systems facilitate our communication and access to information, taking down language barriers. It is a well-researched area of Natural Language Processing (NLP), especially for resource-rich languages (e.g., language pairs in Europarl Parallel corpus). Besides these languages, there is also work on other language pairs including the Bangla-English language pair. In the current study, we aim to revisit both Statistical Machine Translation (SMT) and Neural Machine Translation (NMT) approaches using well-known, publicly available corpora for the Bangla-English (Bangla to English) language pair. We reported how the performance of the models differ based on the data and modeling techniques; consequently, we also compared the results obtained with Google's machine translation system. Our findings, across different corpora, indicates that NMT based approaches outperform SMT systems. Our results also outperform existing baselines by a large margin.},
keywords = {Bangla-to-English, English-to-Bangla, Machine Translation, Neural Machine Translation, Statistical Machine Translation},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{chowdhury2018towards,
title = {Towards Bangla Named Entity Recognition},
author = {Shammur Absar Chowdhury and Firoj Alam and Naira Khan},
url = {https://www.researchgate.net/profile/Shammur_Chowdhury2/publication/329472241_Towards_Bangla_Named_Entity_Recognition/links/5c0a684ba6fdcc494fe0b126/Towards-Bangla-Named-Entity-Recognition.pdf},
year  = {2018},
date = {2018-01-01},
booktitle = {2018 21st International Conference of Computer and Information Technology (ICCIT)},
pages = {1--7},
organization = {IEEE},
abstract = {Named Entity Recognition is one of the fundamental problems for Information Extraction and the task is to find the mentioned entities in text. Over the years there has been significant progress in Named Entity Recognition (NER) research for resource-rich languages such as English, Chinese, and Italian. Although, there are a number of studies for Bangla NER, however, most of these studies are conducted almost a decade ago and were focused on a single geographical location (i.e., India). Therefore, in this paper, we present a corpus annotated with seven named entities with a particular focus on Bangladeshi Bangla. It is a part of the development of the Bangla Content Annotation Bank (B-CAB). We also present baseline results, which can be useful for future research. For the baseline results, we employed word-level, POS, gazetteers and contextual features along with Conditional Random Fields (CRFs). Our study also includes the exploration of deep neural networks. Additionally, we investigated another large corpus from a different geographical location (i.e., India) and concluded on the importance of geographic-based NER for a language.},
keywords = {Bangla, CRF, LSTM, Named Entity Recognition, Neural Network, Sequence Labeling},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{aridMT2018,
title = {A Collaborative Platform to Collect Data for Machine Translation System},
author = {Arid Hasan and Firoj Alam and Sheak RH and Noori},
year  = {2018},
date = {2018-01-01},
booktitle = {2018 International Joint Conference on Computational Intelligence - IJCCI},
organization = {Springer},
abstract = {The emergence of neural machine translation techniques has opened up a new era for developing translation systems. However, it requires a very large amount of parallel corpus, which are scarce for many under-resourced languages, e.g., Bangla. In order to develop a corpus, currently there is a lack of open-sourced publicly available collaborative system. In this paper, we report an online collaborative system for the development of the parallel corpus. The system is developed for supporting any language, however, we only evaluated for developing Bangla-English parallel corpus. In a task completion evaluation experiment, the system outperforms the widely used offline system i.e., OmegaT.},
keywords = {Collaborative Platform, Machine Translation},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{chowdhury2017bangla,
title = {Bangla grapheme to phoneme conversion using conditional random fields},
author = {Shammur Absar Chowdhury and Firoj Alam and Naira Khan and Sheak RH Noori},
url = {https://www.academia.edu/35648519/Bangla_Grapheme_to_Phoneme_Conversion_Using_Conditional_Random_Fields},
year  = {2017},
date = {2017-01-01},
booktitle = {2017 20th International Conference of Computer and Information Technology (ICCIT)},
pages = {1--6},
publisher = {IEEE},
organization = {IEEE},
abstract = {Integrated with handheld devices, toys, KIOSKs, and call centers, Text to Speech (TTS) and Speech Recognition (SR) have become widely used applications in everyday life. One of the core components of said applications is Grapheme to Phoneme (G2P) conversion. The task at hand is the mapping of the written form to the spoken form, i.e. mapping one sequence to another. In Natural Language Processing (NLP), it is typically referred to as a sequence to sequence labeling task. The task however, is a language dependent one and has primarily been implemented for English and similar resource-rich languages. In comparison, very little has been done for digitally under-resourced languages such as Bangla (ethnonym: Bangla; exonym: Bengali). The current state-of-the-art Bangla Grapheme to Phoneme conversion is limited to rule-based and lexicon based approaches, the development of which requires a significant contribution of linguistic experts.  In this paper, we propose a data-driven machine learning approach for Bangla G2P conversion. We evaluate the existing rule based approaches and design a machine learning model using Conditional Random Fields (CRFs).  To train the machine learning models we have only used character level contextual features due to the fact that extracting hand crafted features requires specialized knowledge. We have evaluated the systems using two publicly available datasets. We have obtained promising results with a phoneme error rate of 1.51% and 14.88% for CRBLP and Google pronunciation lexicons, respectively.},
keywords = {Bangla, Conditional Random Fields, Grapheme to Phoneme (G2P), Pronunciation Generation},
pubstate = {published},
tppubtype = {inproceedings}
}
@article{celli2016mood,
title = {In the mood for sharing contents: Emotions, personality and interaction styles in the diffusion of news},
author = {Fabio Celli and Arindam Ghosh and Firoj Alam and Giuseppe Riccardi},
year  = {2016},
date = {2016-01-01},
journal = {Information Processing & Management},
volume = {52},
number = {1},
pages = {93--98},
publisher = {Elsevier},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
@inproceedings{Celli2016b,
title = {Multilevel Annotation of Agreement and Disagreement in Italian News Blogs},
author = {Celli Fabio and Riccardi Giuseppe and Alam Firoj},
year  = {2016},
date = {2016-01-01},
booktitle = {Proc. LREC},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2016bidirectional,
title = {Bidirectional lstms\textemdashcrfs networks for bangla pos tagging},
author = {Firoj Alam and Shammur Absar Chowdhury and Sheak Rashed Haider Noori},
url = {https://ieeexplore.ieee.org/document/7860227/},
year  = {2016},
date = {2016-01-01},
booktitle = {2016 19th International Conference on Computer and Information Technology (ICCIT)},
pages = {377--382},
organization = {IEEE},
abstract = {Part-of-speech (POS) information is one of the fundamental components in the natural language processing pipeline, which helps in extracting higher-level information such as named entities, discourse, and syntactic structure of a sentence. For some languages, such as English, Dutch, and Chinese, it is considered as a solved problem due to the higher accuracy (97%) of the predicted system. Significant efforts have been made for such languages in terms of making the data publicly accessible and also organizing evaluation campaigns. Compared to that there are very fewer efforts for Bangla (ethnonym: Bangla; exonym: Bengali). In this paper, we present a knowledge poor approach for POS tagging, which we evaluated using publicly accessible dataset from LDC. The motivation of our approach is that we did not want to rely on any existing resources such as lexicon or named entity recognizer for designing the system as they are not publicly available and difficult to develop. We have not used any hand-crafted features, rather we employed distributed representations of word and characters. We designed the system using Long Short Term Memory (LSTM) neural networks followed by Conditional Random Fields (CRFs) for designing the model with an inclusion of pre-trained word embedded model. We obtained promising results with an accuracy of 86.0%, F1 of 86.25%. },
keywords = {Bangla, Deep Learning},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{danieli2015emotion,
title = {Emotion unfolding and affective scenes: A case study in spoken conversations},
author = {Morena Danieli and Giuseppe Riccardi and Firoj Alam},
year  = {2015},
date = {2015-01-01},
booktitle = {Proceedings of the International Workshop on Emotion Representations and Modelling for Companion Technologies},
pages = {5--11},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alamRE2015,
title = {A Knowledge-Poor Approach to BioCreative V DNER and CID Tasks},
author = {Firoj Alam and Anna Corazza and Alberto Lavelli and Roberto Zanoli},
year  = {2015},
date = {2015-01-01},
booktitle = {In Proc. of the Fifth BioCreative Challenge Evaluation Workshop},
pages = {274-279},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{stepanovautomatic2015,
title = {Automatic Summarization of Call-center Conversations},
author = {E Stepanov and B Favre and F Alam and S Chowdhury and K Singla and J Trione and F B\'{e}chet and G Riccardi},
year  = {2015},
date = {2015-01-01},
booktitle = {In Proc. of the IEEE Automatic Speech Recognition and Understanding Workshop (ASRU 2015)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{morena2015,
title = {Emotion Unfolding and Affective Scenes: A Case Study in Spoken Conversations},
author = {Morena Danieli and Giuseppe Riccardi and Firoj Alam},
year  = {2015},
date = {2015-01-01},
booktitle = {Proc. of Emotion Representations and Modelling for Companion Systems (ERM4CT) 2015,},
publisher = {ICMI},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inbook{alam2015comparing,
title = {Comparing Named Entity Recognition on Transcriptions and Written Texts, Harmonization and Development of Resources and Tools for Italian Natural Language Processing within the PARLI Project},
author = {Firoj Alam and Bernardo Magnini and Roberto Zanoli},
editor = {R Basili and C Bosco and R Delmonte and A Moschitti and M Simi},
year  = {2015},
date = {2015-01-01},
journal = {Vol. 589},
volume = {589},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
@inproceedings{danieli2014empathyannotation,
title = {Annotation of Complex Emotions in Real-Life Dialogues: The Case of Empathy},
author = {Morena Danieli and Giuseppe Riccardi and Firoj Alam},
editor = {Bernardo Magnini Roberto Basili Alessandro Lenci},
year  = {2014},
date = {2014-12-01},
booktitle = {First Italian Conference on Computational Linguistics CLiC-it 2014},
volume = {Vol. I},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2014icassp,
title = {Fusion of Acoustic, Linguistic and Psycholinguistic Features for Speaker Personality Traits Recognition},
author = {Firoj Alam and Giuseppe Riccardi},
year  = {2014},
date = {2014-05-01},
booktitle = {ICASSP2014 - SLTC},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{morena2014,
title = {Annotation of Complex Emotion In Real-Life Dialogues},
author = {Morena Danieli and Giuseppe Riccardi and Firoj Alam},
editor = {Roberto Basili and Alessandro Lenci and Bernardo Magnini},
year  = {2014},
date = {2014-01-01},
booktitle = {Proc. of 1st Italian Conf. on Computational Linguistics (CLiC-it) 2014},
volume = {1},
number = {122--127},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{chowdhury2014overlap,
title = {Unsupervised Recognition and Clustering of Speech Overlaps in Spoken Conversations},
author = {Shammur A Chowdhury and Giuseppe Riccardi and Firoj Alam},
year  = {2014},
date = {2014-01-01},
booktitle = {Workshop on Speech, Language and Audio in Multimedia (SLAM 2014)},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2014predicting,
title = {Predicting Personality Traits using Multimodal Information},
author = {Firoj Alam and Giuseppe Riccardi},
year  = {2014},
date = {2014-01-01},
booktitle = {Proceedings of the 2014 ACM Multi-Media on WCPR14},
pages = {15-18},
organization = {ACM},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2013personalityb,
title = {Comparative Study of Speaker Personality Traits Recognition in Conversational and Broadcast News Speech},
author = {Firoj Alam and Giuseppe Riccardi},
year  = {2013},
date = {2013-01-01},
booktitle = {INTERSPEECH},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{Ig,
title = {Comparative Study of Speaker Personality Traits Recognition in Conversational and Broadcast News Speech},
author = {Firoj Alam and Giuseppe Riccardi},
year  = {2013},
date = {2013-01-01},
booktitle = {INTERSPEECH},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2013personalityb,
title = {Personality Traits Recognition on Social Network-Facebook},
author = {Firoj Alam and Evgeny A Stepanov and Giuseppe Riccardi},
year  = {2013},
date = {2013-01-01},
booktitle = {Proc of Workshop on Computational Personality Recognition, AAAI Press, Melon Park, CA},
pages = {6--9},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inbook{alam2013combination,
title = {A Combination of Classifiers for Named Entity Recognition on Transcription},
author = {Firoj Alam and Roberto Zanoli},
editor = {Bernardo Magnini and Francesco Cutugno and Mauro Falcone and Emanuele Pianta},
year  = {2013},
date = {2013-01-01},
booktitle = {Evaluation of Natural Language and Speech Tools for Italian},
pages = {107--115},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
@inproceedings{alam2012ner,
title = {EVALITA 2011: Named Entity Recognition on Transcription using cascaded classifiers},
author = {Firoj Alam},
year  = {2012},
date = {2012-01-01},
booktitle = {Working Notes of EVALITA 2011},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{murtoza2011phonetically,
title = {Phonetically Balanced Bangla Speech Corpus},
author = {SM Murtoza and Firoj Alam and Rabia Sultana and Shammur Absar and Mumit Khan},
url = {https://pdfs.semanticscholar.org/582a/5acf08bcc3c03264a25d2bc2b75718ef24ff.pdf},
year  = {2011},
date = {2011-01-01},
booktitle = {Conference on Human Language Technology for Development},
abstract = {This paper describes the development of a phonetically balanced Bangla speech corpus. Construction of speech applications such as text to speech and speech recognition requires a phonetically balanced speech database in order to obtain a natural output. Here we elicited text collection procedure, text normalization,
G2P conversion and optimal text selection using a greedy selection method and hand pruning.},
keywords = {Bangla Balanced corpus, Phonetics, Speech Recognition, Speech Synthesis},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2011bangla,
title = {Bangla Text to Speech using Festival},
author = {Firoj Alam and SM Murtoza Habib and Mumit Khan},
url = {https://www.academia.edu/2955759/Bangla_Text_to_Speech_using_Festival},
year  = {2011},
date = {2011-01-01},
booktitle = {Conference on Human Language Technology for Development (HLTD 2011), Alexandria, Egypt},
pages = {02--05},
abstract = {This paper describes the development of the first, usable, open source and freely available Bangla Text to Speech (TTS) system for Bangladeshi Bangla using the open source Festival TTS engine. Besides that, this paper also discusses a few practical applications that use this system. This system is developed using diphone concatenation approach in its waveform generation phase. Construction of a diphone database and implementation of the natural language processing modules are described.},
keywords = {Bangla Speech Synthesis, Bangla Text To Speech},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2010development,
title = {Development of annotated Bangla speech corpora},
author = {Firoj Alam and SM Habib and Dil Afroza Sultana and Mumit Khan},
url = {https://www.researchgate.net/publication/47528757_Development_of_annotated_Bangla_speech_corpora},
year  = {2010},
date = {2010-01-01},
booktitle = {Spoken Language Technologies for Under-resourced language},
abstract = {This paper describes the development procedure of three different Bangla read speech corpora which can be used for phonetic research and developing speech applications. Several criteria were maintained in the corpora development process that includes considering the phonetic and prosodic features during text selection. On the other hand, a specification was maintained in the recording phase as the speaking style is a vital part in speech applications. We also concentrated on proper text normalization, pronunciation, aligning, and labeling. The labeling was done manually \textendash in the present endeavor sentence level labeling (annotation) was completed by maintaining a specification so that it could be expanded in future.},
keywords = {Phonetic research, Speech corpora, Speech processing},
pubstate = {published},
tppubtype = {inproceedings}
}
@techreport{chowdhury2010implementation,
title = {Implementation of Speech Recognition System for Bangla},
author = {Shammur Absar Chowdhury},
url = {https://www.researchgate.net/publication/277671513_Implementation_of_speech_recognition_system_for_Bangla},
year  = {2010},
date = {2010-01-01},
institution = {BRAC University},
school = {BRAC University},
abstract = {Speech recognition and understanding of spontaneous speech have been a goal of research since 1970. It is a process of conversion of speech to text. The object of human speech is not just a way to convey words from one person to another but also to make the other person to understand the depth of the spoken words. For understanding speech human not only consider for information passed to the ears but also judge the information by the context of the information. That’s why human can easily understand the spoken language convey to them even in noisy environment. Recognizing speech by machine is so difficult for the dynamic characteristics of spoken languages. People used different approaches for automated speech recognition system. For recognizing speech people always prefer English as most of the research and implemented for them. So I am intended to have my research on Continuous Speech Recognition (CSR) system but preferably in our mother tongue \textendashBangla. It is an area where a lot to contribute for our language to establish in computer field.
So in this Thesis semester, my contribution is to show how to use CMU-Sphinx tools to build a domain based continuous speech recognition system, what is the methodology; from preparing text to speech corpus, training and integrating it with the system. Then the work is also extended to test the CSR in various environments in basic level. },
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
@inproceedings{alam2008text,
title = {Text normalization system for Bangla},
author = {Firoj Alam and SM Habib and Mumit Khan},
year  = {2009},
date = {2009-01-01},
booktitle = {Conference on Language and Technology},
institution = {Center for research on Bangla language processing (CRBLP), BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{hasnat2009integrating,
title = {Integrating Bangla script recognition support in Tesseract OCR},
author = {Md Hasnat and Muttakinur Rahman Chowdhury and Mumit Khan and others},
year  = {2009},
date = {2009-01-01},
publisher = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{hasnat2009rule,
title = {Rule based segmentation of lower modifiers in complex Bangla scripts},
author = {Md Hasnat and Mumit Khan and others},
year  = {2009},
date = {2009-01-01},
publisher = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{hasnat2009elimination,
title = {Elimination of splitting errors in printed Bangla scripts},
author = {Md Abul Hasnat and Mumit Khan},
url = {https://www.researchgate.net/publication/228583706_Elimination_of_splitting_errors_in_printed_Bangla_scripts},
year  = {2009},
date = {2009-01-01},
booktitle = {Proc. of the Conference on Language & Technology},
pages = {22--24},
abstract = {Accurate and robust character segmentation is a significant challenge in Bangla optical character recognition (OCR). The two main errors in segmentation are joining and splitting errors. To solve the problems of joining errors, several algorithms have been proposed in the literature, with varying degrees of accuracy. Few solutions have been proposed to handle the splitting error issue; however, the accuracy of these proposed solutions were not measured. In an actual implementation of the proposed techniques, we observe the presence of over segmented units. In this paper, we present a dissection based splitting error elimination method which solves the problem of over segmentation under a wide range of document images. Our methodology performs its tasks in two stages: we first concentrate on the careful clipping of the matraa (headline) and put our effort in keeping the pixel information of the units intact which are sensitive to splitting errors. In the second stage, we apply several rules based on the feature information of the units in a word. The combined performance of these two stages results in success rate of 99.93% in eliminating the splitting errors.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{alam2008acoustic,
title = {Acoustic Analysis of Bangla Consonants},
author = {Firoj Alam and SM Murtoza Habib and Mumit Khan},
year  = {2008},
date = {2008-01-01},
booktitle = {Proc. Spoken Language Technologies for Under-resourced language (SLTU'08)},
pages = {5--7},
address = {Vietnam},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{hasnat2008high,
title = {A high performance domain specific OCR for Bangla script},
author = {Md Abul Hasnat and SM Murtoza Habib and Mumit Khan},
year  = {2008},
date = {2008-01-01},
booktitle = {Novel Algorithms and Techniques in Telecommunications, Automation and Industrial Electronics},
pages = {174--178},
publisher = {Springer},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@techreport{alam2008textb,
title = {Text normalization system for Bangla},
author = {Firoj Alam and SM Habib and Mumit Khan},
year  = {2008},
date = {2008-01-01},
institution = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {techreport}
}
@inproceedings{alam2007text,
title = {Text to speech for Bangla language using festival},
author = {Firoj Alam and Promila Kanti Nath and Dr Mumit Khan},
year  = {2007},
date = {2007-01-01},
booktitle = {Proc. 1st Intl. Conf. on Digital Comm. and Computer Applications},
volume = {1},
pages = {853-859},
address = {Amman, Jordan},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{hasnat2007isolated,
title = {Isolated and continuous bangla speech recognition: implementation, performance and application perspective},
author = {Md Hasnat and Jabir Mowla and Mumit Khan and others},
year  = {2007},
date = {2007-01-01},
publisher = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@proceedings{hasnat2007segmentation,
title = {Segmentation free Bangla OCR using HMM: Training and Recognition},
author = {Md Hasnat and SM Habib and Mumit Khan and others},
year  = {2007},
date = {2007-01-01},
publisher = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
@inproceedings{habib2006skew,
title = {Skew angle detection of Bangla script using Radon transform},
author = {SM Habib and Nawsher Ahamed Noor and Mumit Khan},
year  = {2006},
date = {2006-01-01},
publisher = {BRAC University},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}