International Journal of Innovative Research in Engineering最新文献_第6页

ML-Driven Facial Synthesis from Spoken Words Using Conditional GANs 使用条件 GAN 从口语中提取 ML 驱动的面部合成

International Journal of Innovative Research in Engineering Pub Date : 2024-01-25 DOI: 10.59256/ijire.20240501004

Vaishnavi Srivastava, Sakshi Srivastava, Sakshi Chauhan, Divyakshi Yadav

引用次数: 0

BLYNK RFID and Retinal Lock Access System BLYNK 射频识别和视网膜锁门禁系统

International Journal of Innovative Research in Engineering Pub Date : 2024-01-24 DOI: 10.59256/ijire.20240501003

Yoheswari S, Adhithyaram L, Gokulesh S, Harish Raj K.B, Jivithesh Harshaa R D

{"title":"BLYNK RFID and Retinal Lock Access System","authors":"Yoheswari S, Adhithyaram L, Gokulesh S, Harish Raj K.B, Jivithesh Harshaa R D","doi":"10.59256/ijire.20240501003","DOIUrl":"https://doi.org/10.59256/ijire.20240501003","url":null,"abstract":"The BLYNK RFID AND RETINAL LOCKACCESS SYSTEM describes a digital door lock system that uses an ESP32-CAM module, which is a budget friendly development board with a very small size camera and a micro-SD card slot. The system uses retinal recognition technology to detect the retinal of the person who wants to access the door. The AI-Thinker ESP32-CAM module takes pictures of the person and sends them to the owner via the BLYNK application installed on their mobile phone. The owner can then grant permission to access the door based on the person’s identity. When deploying your BLYNK RFID and retinal scanner project, it's important to consider scalability and maintenance. As your user base and access requirements may change over time, plan for future expansion and updates. Regularly review and update your system's firmware, libraries, and security measures to stay ahead of potential vulnerabilities and evolving best practices in access control. Monitoring and auditing your system's usage is crucial. The Blynk platform can help you gather data on access attempts and system performance, allowing you to analyze the data for any anomalies and potential security breaches. This data can be valuable for compliance, troubleshooting, and performance optimization. Key Word: retinal and RFID scanning for lock to authentic users, using an ESP32-CAM and RFID reader controlling through BLYNK.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140497224","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

Custom Voice Cloner 自定义语音克隆器

International Journal of Innovative Research in Engineering Pub Date : 2024-01-19 DOI: 10.59256/ijire.20240501002

Usharani K, Nandha kumaran H, Nikhilesh Pranav M.S, Nithish kumar K.K, Prasanna Krishna A.S

{"title":"Custom Voice Cloner","authors":"Usharani K, Nandha kumaran H, Nikhilesh Pranav M.S, Nithish kumar K.K, Prasanna Krishna A.S","doi":"10.59256/ijire.20240501002","DOIUrl":"https://doi.org/10.59256/ijire.20240501002","url":null,"abstract":"The Custom Voice Cloner is based on voice signal speech synthesizer. It is a technology that converts text into audible speech, simulating human speech characteristics like pitch and tone. It finds applications in virtual assistants, navigation systems, and accessibility tools. Building one in Python typically involves Text-to-Speech (TTS) libraries such as gTTS, pyttsx3, or platform-specific options for Windows and macOS, offering easy text-to-speech conversion.However, TTS libraries might lack customization and voice quality needed for advanced projects. For more sophisticated applications, custom voice synthesizers can be built using deep learning techniques like Tacotron and WaveNet. These models learn speech nuances for more natural output.Creating a custom voice synthesizer is challenging, requiring high-quality training data, machine learning expertise, and substantial computational resources. It goes beyond generating speech to convey emotions and nuances in pronunciation for natural and expressive voices. Key Word: Voice signal speech synthesizer,text-to-speech conversion, deep learning,TTS, gTTS, pyttsx3,etc.","PeriodicalId":516932,"journal":{"name":"International Journal of Innovative Research in Engineering","volume":"427 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140502508","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

Embedding Artificial Intelligence for Personal Voice Assistant Using NLP 利用 NLP 为个人语音助理嵌入人工智能

International Journal of Innovative Research in Engineering Pub Date : 2024-01-06 DOI: 10.59256/ijire.20240501001

Maria Sobana S, R. M, Rajkumar R K, Rajkumar M, Siddarthan S

引用次数: 0