2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)最新文献_第6页

Knowledge Enhancement using Question Generation for Images and Chart Data Input 使用问题生成增强图像和图表数据输入的知识

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064970

D. Tayal, Amit Jain, Nikita Shrivastava, Akshita Jain, Hunny Gaur

引用次数: 0

Detection of Lung Tumor Using Enhanced Image Classification 基于增强图像分类的肺肿瘤检测

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064975

J. Arora, M. Tushir, Poonam Bansal

引用次数: 0

Development of a Context based Conversation State Prediction System 基于上下文的会话状态预测系统的开发

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064944

S. U. Rittikar, Shubham Rangate, U. Nuli, Mugdha A Sathe, Vaidehi Rathor, Divya Patil

引用次数: 0

A Bilingual Machine Transliteration System for Sanskrit-English Using Rule-Based Approach 基于规则的梵文-英语双语机器音译系统

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064993

N. Sethi, A. Dev, Poonam Bansal

{"title":"A Bilingual Machine Transliteration System for Sanskrit-English Using Rule-Based Approach","authors":"N. Sethi, A. Dev, Poonam Bansal","doi":"10.1109/AIST55798.2022.10064993","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10064993","url":null,"abstract":"Machine Transliteration is a big challenging area in an increasingly multilingual ecosphere due to its dangerous position in various downstream natural language processing application systems. When a word is transliterated, it is shifted from one script to another. In contrast to a translation, which clarifies the meaning of a word written in a different language, a transliteration only conveys the word's pronunciation by utilizing a familiar alphabet. This paper proposes a technique for creating a bilingual automated tool to type Sanskrit using English orthography/alphabets and converting Sanskrit text into the script of English which helps in reading the Sanskrit text for those who are not aware about the orthography of Sanskrit language. The system receives input via the QWERTY keyboard, which produces the equivalent Sanskrit text and inversely user can give Sanskrit text as input to get equivalent text using the script of English language. The goal is to create an easy-to-use and robust automated solution that allows end-users to effortlessly type Sanskrit shlokas or sentences using an English keyboard. The suggested approach is unique in that it is based on the language's Unicode and works for the low-resource ancient language Sanskrit. The primary applications of the designed tool are to help user to read Sanskrit text using the script/orthography of English, to create parallel corpora for the Sanskrit language translation process, to create e-versions of manuscripts written in Sanskrit language as the majority of ancient knowledge is not available on the internet, and to make it easy to learn Sanskrit language by any individual or students at the school level. This tool encourages humans to use their original language.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127118639","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

Wind Energy Forecasting Using Artificial Intelligence 利用人工智能进行风能预测

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065273

Shreya Desai, Shlok Sampat, Darshil Vadodaria, Mrunalini Pimpale

引用次数: 0

End-to-End recognition approach for Cognitive Impaired speech using Sequential Conv-Nets 基于顺序卷积神经网络的认知障碍语音端到端识别方法

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064867

Riya Sharma, Saloni Gupta, Pooja Gambhir, Poonam Bansal

{"title":"End-to-End recognition approach for Cognitive Impaired speech using Sequential Conv-Nets","authors":"Riya Sharma, Saloni Gupta, Pooja Gambhir, Poonam Bansal","doi":"10.1109/AIST55798.2022.10064867","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10064867","url":null,"abstract":"It is essential to find a way to early diagnosis of Mental Cognitive Disorders (MCD) in order to enable preventative care and prompt therapy to stop future progression. Automatic speech recognition software (ASR) giving transcriptions could possibly enhance communication of speech in the present. ASR is especially beneficial for those with increasing conditions that limit the comprehensibility of speech issues with motor function. ASR services typically have training on normal speech and might not be ideal for speech impairment, putting up a roadblock to using augmented help tools. This paper presents the recognition of cognitive impaired speech using Sequential 2-dimensional Conv-Nets. Convolutional networks efficiently explore and exploits temporal, cepstral and spectral structures of the speech signals. The network has been trained and tested on Spectrograms of Mel-Filters banks taking its time and frequency variants. The experiment was performed on 15000 spoken responses of digits (0-9) uttered by Dementia patients. The outcome of the trained model showed a validation accuracy of 91.27% with a loss of 0.5%.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134219663","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

Fuzzy and Machine learning Classifiers for Hate Content Detection: A Comparative Analysis 模糊分类器与机器学习分类器在仇恨内容检测中的比较分析

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10064822

Anusha Chhabra, D. Vishwakarma

引用次数: 0

Cognitive-Chair: AI based advanced Brain Sensing Wheelchair for Paraplegic/Quadriplegic people 认知椅:基于人工智能的高级脑感应轮椅，适用于截瘫/四肢瘫痪患者

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065338

Kshitij Joshi, Pujan Soni, Smit Joshi, Abhilasha Vyas, Rudra Joshi

{"title":"Cognitive-Chair: AI based advanced Brain Sensing Wheelchair for Paraplegic/Quadriplegic people","authors":"Kshitij Joshi, Pujan Soni, Smit Joshi, Abhilasha Vyas, Rudra Joshi","doi":"10.1109/AIST55798.2022.10065338","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065338","url":null,"abstract":"This paper presents a system wherein the individual seated on a wheelchair will be given a keen headband to control the wheelchair based on neural signals or brain waves emitted from the brain utilizing technologies like Brain-Computer Interface(BCI), Electrooculography (EOG) and Electroencephalography (EEG). Subsequent to applying these technologies on a small wheelchair model, we have gotten incredible accuracy of the neural-signals. Thus the results are quite astonishing. Apart from this, in future aspects considering the safety of passengers, if anything obstructing the way of the wheelchair comes too close; causing the person to lose their concentration, the wheelchair will sense the obstacle and will apply brakes immediately. Other smart mobility features like fall-detection, ability to go through tight spaces, autonomous driving features can also be seen. The proposed wheelchair has the potential to significantly impact the healthcare business. The use of this brain-controlled wheelchair can improve a wheelchair-worthy patient's quality of life.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132242156","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

Vibing: The Mood Based Music Recommendation System Vibing:基于情绪的音乐推荐系统

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065377

Garima, Shreya Thapliyal, Bhargavi Bhatia, Ritika Tyagi, Vivekanand Jha, Rakesh Kumar Singh

引用次数: 0

Dynamic Android Malware Detection Using Light Gradient Boosting Machine 基于光梯度增强机的Android恶意软件动态检测

2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST) Pub Date : 2022-12-09 DOI: 10.1109/AIST55798.2022.10065236

Vidhi Bansal, Niyati Baliyan, Mohona Ghosh

{"title":"Dynamic Android Malware Detection Using Light Gradient Boosting Machine","authors":"Vidhi Bansal, Niyati Baliyan, Mohona Ghosh","doi":"10.1109/AIST55798.2022.10065236","DOIUrl":"https://doi.org/10.1109/AIST55798.2022.10065236","url":null,"abstract":"Growing popularity of Android smartphones, its vast user base, open architecture, vague permission management system, lack of security standards, absence of reliable app inspection, and increasing use of smartphones in sensitive areas like banking, security, identity management have made Android a lucrative target for malware developers. Android malware is becoming more and more sophisticated with the use of obfuscation techniques rendering the traditional signature based mechanism ineffective. A reliable, robust, efficient, and effective Android malware detection method is required to tackle with this emerging issue. Current techniques lack the are time inefficient and less reliable in terms of accuracy. In this work, we present a efficient, reliable, and robust Android malware detection technique based on light gradient boosting machine. We trained and tested the framework on dynamically extracted features. We have got the accuracy of 98.008%, recall of 99.194%, precision of 98.385%, and F1 score of 98.787%. On implementing the existing state of art techniques, we found that the proposed scheme outperforms them thereby establishing supremacy of our work.","PeriodicalId":360351,"journal":{"name":"2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)","volume":"171 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115471196","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