2019 International Conference on Bangla Speech and Language Processing (ICBSLP)最新文献_第2页

Real-time Bangladeshi Currency Detection System for Visually Impaired Person 孟加拉视障人士即时货币侦测系统

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201518

Md Ferdousur Rahman Sarker, Md. Israfil Mahmud Raju, A. Marouf, Rubaiya Hafiz, S. A. Hossain, Munim Hossain Khandker Protik

{"title":"Real-time Bangladeshi Currency Detection System for Visually Impaired Person","authors":"Md Ferdousur Rahman Sarker, Md. Israfil Mahmud Raju, A. Marouf, Rubaiya Hafiz, S. A. Hossain, Munim Hossain Khandker Protik","doi":"10.1109/ICBSLP47725.2019.201518","DOIUrl":"https://doi.org/10.1109/ICBSLP47725.2019.201518","url":null,"abstract":"This paper presents a real-time Bangladeshi currency detection system for visually impaired persons. The proposed system exploits the image processing algorithms to facilitate the visually impaired people to prosperously recognize banknotes. The recent banknotes of Bangladesh have blind embossing or blind dots, which could be effective to recognize the value of the bill by touching. As the embossing fades away in the long-term used notes, detecting right value of the banknote using image processing algorithms could be considered as a challenging task. Particularly in Bangladesh, each banknote seems similar using the direct exertion of simplified image processing algorithms. In this paper, a recognition system was implemented that can detect Bangladeshi banknote in different viewpoints and scales. The detection system is also able to detect currency those are rumpled, decrepit or even worn. The detection system includes image preprocessing, image analysis and image recognition. To enhance the determination of currency recognition, the descriptor of an individual input scene is matched with various training images of the same category. After that, by analyzing their matching result it recognizes the currency with higher confidence. For real-time recognition, we have deployed the system into a mobile application.","PeriodicalId":413077,"journal":{"name":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124338854","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Handwritten Bengali Number Detection using Region Proposal Network 基于区域建议网络的手写体孟加拉数字检测

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.202049

Shaharat Tajrean, Mohammad Abu Yousuf

{"title":"Handwritten Bengali Number Detection using Region Proposal Network","authors":"Shaharat Tajrean, Mohammad Abu Yousuf","doi":"10.1109/ICBSLP47725.2019.202049","DOIUrl":"https://doi.org/10.1109/ICBSLP47725.2019.202049","url":null,"abstract":"As a seventh most spoken native language, Bengali needs a robust and accurate optical character recognition (OCR) especially for number detection. As there is no publicly available well-organized dataset for Bangla number OCR, a synthesized dataset was generated to fill the lack of available data. The recent advancement in artificial intelligence using deep neural networks easily outperforms prior hand selected feature-based machine learning approaches. As the region proposal networks (RPN) in deep neural networks perform very well in detecting objects, it can be used for digit detection in an image. So, in this work a very robust Bengali handwritten number detection system is presented where with the help of deep neural networks and a very well-organized, unbiased generated dataset we achieved state of the art result in handwritten Bangla number detection. This system beats any related prior works by a large margin while considering a real world dataset for benchmarks. The overall detection accuracy was 97.8%. The processing can be done real-time with about 35 images per second using a GPU. Also, while implementing the solution is completely based on python, the framework used for deep learning is Google’s Tensorflow and the dependencies, all of which are publicly available.","PeriodicalId":413077,"journal":{"name":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115914424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Automatic Detection of Satire in Bangla Documents: A CNN Approach Based on Hybrid Feature Extraction Model 孟加拉文讽刺文章自动检测:一种基于混合特征提取模型的CNN方法

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201517

Arnab Sen Sharma, Maruf Ahmed Mridul, Md. Saiful Islam

引用次数: 12

Intrinsic Evaluation of Bangla Word Embeddings 孟加拉语词嵌入的内在评价

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201506

Nafiz Sadman, Akib Sadmanee, Md. Iftekhar Tanveer, Md. Ashraful Amin, A. Ali

{"title":"Intrinsic Evaluation of Bangla Word Embeddings","authors":"Nafiz Sadman, Akib Sadmanee, Md. Iftekhar Tanveer, Md. Ashraful Amin, A. Ali","doi":"10.1109/ICBSLP47725.2019.201506","DOIUrl":"https://doi.org/10.1109/ICBSLP47725.2019.201506","url":null,"abstract":"Word embeddings are vector representations of word that allow machines to learn semantic and syntactic meanings by performing computations on them. Two wellknown embedding models are CBOW and Skipgram. Different methods proposed to evaluate the quality of embeddings are categorized into extrinsic and intrinsic evaluation methods. This paper focuses on intrinsic evaluation - the evaluation of the models on tasks, such as analogy prediction, semantic relatedness, synonym detection, antonym detection and concept categorization. We present intrinsic evaluations on Bangla word embedding created using CBOW and Skipgram models on a Bangla corpus that we built. These are trained on more than 700,000 articles consisting of more than 1.3 million unique words with different embedding dimension sizes, e.g., 300, 100, 64, and 32. We created the evaluation datasets for the abovementioned tasks and performed a comprehensive evaluation. We observe, word vectors of dimension 300, produced using Skipgram models, achieves accuracy of 51.33% for analogy prediction, a correlation of 0.62 for semantic relatedness, and accuracy of 53.85% and 9.56% for synonym and antonym detection 9.56%. Finally, for concept categorization the accuracy is 91.02%. The corpus and evaluation datasets are made publicly available for further research.","PeriodicalId":413077,"journal":{"name":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","volume":"19 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129070756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Development of a Bangla Sense Annotated Corpus for Word Sense Disambiguation 孟加拉语语义标注语料库的开发与应用

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201516

Monisha Biswas, M. M. Hoque

引用次数: 2

End to End Parts of Speech Tagging and Named Entity Recognition in Bangla Language 孟加拉语端到端词性标注与命名实体识别

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201541

Jillur Rahman Saurav, Summit Haque, Farida Chowdhury

{"title":"End to End Parts of Speech Tagging and Named Entity Recognition in Bangla Language","authors":"Jillur Rahman Saurav, Summit Haque, Farida Chowdhury","doi":"10.1109/ICBSLP47725.2019.201541","DOIUrl":"https://doi.org/10.1109/ICBSLP47725.2019.201541","url":null,"abstract":"Automatic Parts of Speech(POS) tagging is one of the most fundamental tasks for a language in Natural Language Processing(NLP), which acts as a feature for solving advanced NLP tasks. Named Entity Recognition(NER) is another essential task of NLP for information retrieval. Researchers could not find up to the mark solution yet on these two tasks for Bangla language compared to other languages, for instance, English, Ger-man. Moreover, many solutions heavily depend on handcrafted features that require strong linguistic expertise. As these two sequence labeling tasks are similar, In this work, two different datasets of POS tagging and NER were prepared, and different deep neural network approaches studied for solving these two tasks separately. All of the approaches were end to end and did not need any handcrafted feature like word suffixes or affixes, gazetteers, dictionary. This study came up with an end to end solution using deep neural network-based model consisting of Bi-directional Long short-term memory(BLSTM), Convolutional Neural Network(CNN) and Conditional Random Field(CRF). The proposed model trained on respected datasets achieved an accuracy of 93.86% on POS tagging and a strict f1 score of 0.6285 on NER on prepared datasets, respectively.","PeriodicalId":413077,"journal":{"name":"2019 International Conference on Bangla Speech and Language Processing (ICBSLP)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133244670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A model of diphone duration for speech synthesis in Bangla 孟加拉语语音合成的双音持续时间模型

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201469

K. Swarna, M. S. Rahman

引用次数: 0

Analyzing Sentiment of Movie Reviews in Bangla by Applying Machine Learning Techniques 应用机器学习技术分析孟加拉语电影评论的情感

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201483

Rumman Rashid Chowdhury, M. Shahadat Hossain, S. Hossain, Karl Andersson

引用次数: 26

Sentimental Style Transfer in Text with Multigenerative Variational Auto-Encoder 基于多生成变分自动编码器的文本情感风格转换

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201508

Md. Palash, P. Das, Summit Haque

引用次数: 5

Neural vs Statistical Machine Translation: Revisiting the Bangla-English Language Pair 神经机器翻译与统计机器翻译:重新审视孟加拉语-英语语言对

2019 International Conference on Bangla Speech and Language Processing (ICBSLP) Pub Date : 2019-09-01 DOI: 10.1109/ICBSLP47725.2019.201502

Md. Arid Hasan, Firoj Alam, S. A. Chowdhury, Naira Khan

引用次数: 7