DEEP LEARNING MODEL Use_of_AI_and_Bhashini.pptx

BHASHINI LANGUAGE MODEL

1. Use of AI and Bhashini Enhancing Language and Communication with Artificial Intelligence Kavita Bhatnagar Tarun Bairathi

2. Introduction to AI Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. Key areas of AI: Machine Learning, Natural Language Processing (NLP), Computer Vision, Robotics

3. More Definitions

4. Brief History of AI Development

5. Surveillance and Privacy Invasion – Mass surveillance & Facial Recognition Lethal Autonomous Weapons Systems (LAWS) Bias &Discrimination- Algorithmic Bias Job Displacement – Economic Inequality Misinformation & DeepFakes Cyber security threats – AI driven Cyber Attacks Ethical Dilemmas – Lack of Accountability Loss of human skills & creativity

6. Healthcare: Diagnostics, treatment recommendations, patient monitoring Finance: Fraud detection, algorithmic trading, personalized banking Retail: Customer service chatbots , personalized recommendations, inventory management Transportation: Self-driving cars, traffic management, predictive maintenance Entertainment: Content recommendation, virtual assistants, interactive games Education: Personalized learning and Administrative Automation Manufacturing: - Quality Control & Supply Chain Optimization Public Safety – Disaster Response, Crime Prevention and Emergency Services Environment and sustainability – Climate Modeling, Energy Management & Wild life Conservation

7. Bhashini’s Unified Vision “Harness natural language technologies to enable a diverse ecosystem of contributors, partnering entities and citizens for the purpose of transcending language barriers, thereby ensuring digital inclusion and digital empowerment in an Aatma Nirbhar Bharat” Bhashini’s Unified Mission “Create a knowledge-based society by transcending the language barriers and providing content and services to citizens, in their own language, both in the form of speech and text.”

8. Introduction to Bhashini is an abbreviation for Bhasha Interface for India. Launched in 2022 Bhashini is a language technology platform that leverages AI to enhance communication and accessibility in multiple languages The Digital India Bhashini Division (DIBD) comes under the Digital India Corporation, which is a section 8 Company under the Ministry of Electronics and Information Technology, Government of India Objective: To bridge language barriers and promote linguistic diversity in a multi linguistic country like India

9. Key Features of Bhashini Language Translation: Real-time text and speech translation across various languages Voice Recognition: Accurate speech-to-text conversion in multiple languages Text-to-Speech: Natural-sounding voice output for written text Language Learning: Tools and resources for learning new languages

10. Factors Leading to Bhashini Lingusitic Diversity Digital inclusion Advancements in AI Government’s Initiatives Global Communication Needs Technological innovations

11. Objectives Enhancing Communication Promoting Linguistic Diversity Improving Accessibility Supporting language learning

12. Bhashini and AI Integration of AI in Bhashini Natural Language Processing (NLP) for understanding and generating human language. Machine Learning algorithms for improving translation accuracy and voice recognition. Deep Learning models for enhancing text-to-speech quality. Optical Character Recognition

13. Natural Language Processing (NLP) Language Understanding:: AI-powered NLP algorithms are used to understand and interpret human language. Sentiment Analysis: NLP can analyze the sentiment behind the text, which is useful for understanding the tone and emotion conveyed. Machine Translation Real-time Translation: AI enables real-time translation of text and speech across various languages. Context-aware Translation: AI models can consider the context of sentences to provide more accurate and relevant translations, improving the overall user experience. Speech Recognition Voice-to-Text Conversion: AI-driven speech recognition systems can accurately convert spoken language into written text. Contd …

14. Text-to-Speech (TTS) Natural-sounding Speech:** AI is used to generate natural-sounding voice output(in different language and dialects) from written text. Deep learning models, such as WaveNet , are employed to create realistic and human-like voices. Optical Character Recognition (OCR) AI-powered OCR technology can extract text(in multiple languages) from images, scanned documents, and handwritten notes. This is particularly useful for translating printed or handwritten materials. Language Learning and Educational Tools Interactive Learning: AI-driven language learning tools can provide personalized learning experiences, adapting to the user's proficiency level and learning pace. Pronunciation Assistance: AI can help users improve their pronunciation by providing real-time feedback and suggestions. Contd …

15. Data Analysis and Insights User Behavior Analysis: AI can analyze user interactions and behavior to gain insights into language usage patterns, preferences, and needs. This information can be used to improve the platform's services. Feedback and Improvement: AI algorithms can analyze user feedback and performance data to continuously improve the accuracy and efficiency of language processing tools. Ethical and Inclusive AI Bias Mitigation: AI models are trained on diverse datasets to minimize biases and ensure fair and accurate language processing across different languages and dialects. Accessibility: AI is used to develop tools that enhance accessibility for users with disabilities, such as speech-to-text for the hearing impaired and text- to-speech for the visually impaired. Contd …

16. Use Cases of Bhashini Education: Multilingual learning materials, language tutoring. Business: Global communication, multilingual customer support. Healthcare: Patient communication in diverse languages, medical transcription. Government Services: Accessibility of information, multilingual public services.

17. Bhashini at Work Data Preparation & API development The initial step involves preparing raw information for analysis, which includes collecting, cleaning, and organizing data. Important details about the data, such as collection dates and content descriptions, are documented for usability. An API is developed, including all necessary components for implementation.  

18. Contd.. API Deployment The API is connected to applications, allowing users to explore data and features interactively. Continuous observation of API performance is conducted, addressing issues as they arise. Insights and knowledge gained during development are documented for future reference.

19. Advantages of Bhashini Improved Communication: Seamless interaction across language barriers. Increased Accessibility: Information and services accessible to non-native speakers. Cultural Preservation: Support for regional and minority languages. Efficiency: Faster and more accurate translations and transcriptions.

20. Challenges and Future Directions Challenges: Handling dialects and regional variations Ensuring high accuracy across all languages Ethical considerations in AI and language processing Future Directions : Expanding language support Enhancing user experience with more intuitive interfaces Collaborations for better data and technology integration

21. Conclusion Summary of Key Points Importance of AI in various sectors Role of Bhashini in promoting multilingual communication Future potential and ongoing challenges

22. Bhashini is a digital symphony, harmonizing with Indian languages. It provides a welcoming embrace of familiarity, offering voice-based access to the digital universe PIB Release at the G 20 Summit, New Delhi