ASL Chatbot: Sign to Speech

@jinufeb14

Building an AI-powered ASL chatbot that seamlessly bridges the gap in communication is a challenge I am passionate about taking on. My experience in computer vision and AI technology, especially with platforms like MediaPipe, TensorFlow, and PyTorch, aligns perfectly with your project's requirements. At #5794 ranking in Freelancer (Under Top 1%), I have earned a strong reputation delivering high-quality, efficient results to my clients. Additionally, I'm no stranger to low-latency web-based applications: I specialize in building real-time systems that prioritize speed without compromising on performance or accuracy. Your requirement for sub-second end-to-end latency matches my ethos perfectly; ensuring your users can communicate fluidly and naturally is of utmost importance. Looking towards future scalability and modularity, I guarantee clean, well-commented code and clear deployment instructions. This proficiency has allowed me to work on diverse projects and quickly adapt to new languages and technologies - something that will come in handy as we expand to other sign languages. Let's collaborate for an inclusive digital world where everyone can communicate effortlessly, regardless of their abilities.

@shadabkhan92

With countless successful projects under our belt, my team and I have earned a reputation for crafting robust AI systems with real-world applications. Our skills go far beyond the theoretical; they are grounded in years of experience implementing functional AI infrastructure capable of making tangible decisions within existing workflows. This is particularly relevant to your project because we know how to leverage AI across various platforms, including web, mobile, and embedded systems. Moreover, our proficiency in NLP, Python, and Speech Synthesis will be instrumental in delivering on your unique requirements. We have previously developed algorithms that recognize natural language patterns, transforming them into meaningful text and the subsequent voice generation component aligns perfectly with your desired ASL-to-speech system. Additionally, we have deployed projects on cloud platforms like AWS, GCP and Azure as well as on devices like ESP32/STM32 using MQTT-connected sensor networks which indicates our potential for delivering a solution that operates smoothly across networks.

@sajjadtaghvaeifr

Hello, I trust you're doing well. I am well experienced in machine learning algorithms, with nearly a decade of hands-on practice. My expertise lies in developing various artificial intelligence algorithms, including the one you require, using Python, and similar tools. I have worked with pytorch, and tensorflow to develop DL models, .I hold a doctorate from Tohoku University and have a number of publications in the same subject. My portfolio, which showcases my past work, is available for your review. Your project piqued my interest, and I would be delighted to be part of it. Let's connect to discuss in detail. Warm regards. please check my portfolio link: https://www.freelancer.com/u/sajjadtaghvaeifr

@Prutheus

Sign-to-speech is a genuinely hard CV problem, so I'll be straight: a reliable ASL chatbot is a staged build, not a weekend demo — and I'd scope v1 honestly rather than overpromise. - Python + a vision model (MediaPipe/OpenCV for hand landmarks) to recognize a defined gesture set first - NLP layer to turn recognized signs into text, then speech synthesis for output - Start with a limited vocabulary that works well, expand from there Proof: I build Python AI pipelines in production — computer-vision and NLP components, document processing, unattended runs. Key question: full ASL or a fixed vocabulary for a specific use case? The scope changes drastically. Realistic v1 in ~10 days. Happy to define it together. Martin

@mayankinnovative

The tension in this project isn't the sign recognition alone, it's holding sub-second latency while running CV inference, text mapping, and speech synthesis as one pipeline inside a browser tab - most ASL demos hit good accuracy but fall apart the moment you add real-time constraints. I'd start with MediaPipe for hand/pose landmark extraction rather than raw frame classification, since landmark-based models are lighter and hit your latency target more reliably than full CNN pipelines on video. That feeds a classifier trained/fine-tuned on ASL alphabet and core vocabulary, with a debouncing layer so partial or transitional signs don't trigger false text output. For speech, I'd stream text to a TTS engine incrementally rather than waiting for full sentences, which is what actually keeps the interaction feeling conversational instead of laggy. On the browser side, I'd handle webcam access and landmark extraction client-side where possible to cut round-trip latency, only sending lightweight data server-side for classification - tested across Chrome, Edge and Firefox specifically, not just Chrome. For deployment, Dockerizing the inference service makes the Ubuntu 22.04 VPS setup straightforward and keeps things modular for mobile or additional sign languages later. Do you have a labeled ASL dataset already, or should sourcing/training data be part of this scope?

@TeraByte26

Hi Hara, I will deliver a browser‑based chatbot that reads ASL signs from the webcam, shows live transcript and plays natural speech within one second, with clean code, deployment guide and demo video. I can ship a functional prototype in three weeks within your budget. Shall I start with a free short video demo? Best regards, Waiting for your response in chat! Best Regards.

@sarimshoaib1425

Hey, this is very doable, But I think a better way to build it would be to use MediaPipe (opensource) because real-time ASL doesn't need a custom CV model trained from scratch, MediaPipe's hand tracking runs right in the browser and gets you fast landmark detection, then a lightweight classifier decides the sign from there. then obviosuly we can feed that into a speech-synthesis engine for the voice output, same kind of real-time pipeline I run for voice AI work already. Easy to host so it stays fast across Chrome, Edge, and Firefox without extra plugins. Can have a working prototype up within a week, full deployment for your VPS included. Let's do it.

@anshumanvermaUK

Hi, I have experience with Python, computer vision, AI/ML pipelines, and browser-based AI integrations. I can build this as a modular pipeline: webcam → gesture detection/classification → text → TTS, with low-latency browser inference where practical. I’d start with a focused pilot for the ASL alphabet/core vocabulary, validate accuracy and latency, then expand the model and vocabulary once the baseline is reliable. I can also handle the web UI, Docker deployment on Ubuntu, testing, and documentation.

@nexvative

Hi, I can build the browser-based ASL recognition and speech system as a modular, low-latency pipeline covering webcam capture → sign recognition → text → natural speech. My proposed approach is to use MediaPipe for efficient hand/pose landmark extraction and a lightweight TensorFlow/PyTorch model for classification, with browser-side inference where practical to minimise latency. The frontend can be built with React/TypeScript, with WebRTC/Web APIs handling the webcam stream and a TTS service providing natural voice output. Key implementation areas: • Train/fine-tune the model using suitable ASL datasets plus your supplied data. • Handle hand position, movement, lighting and camera variations through augmentation and preprocessing. • Add confidence thresholds and temporal smoothing to reduce false recognitions and prevent repeated words. • Display the recognised text in real time and trigger TTS after a completed sign/phrase. • Optimise the pipeline toward the <1-second response target. • Test across Chrome, Edge and Firefox. • Dockerise the application for Ubuntu 22.04/VPS deployment. I’ll provide the complete source code, trained model/inference components, deployment documentation and a working demo. I’ll also report accuracy, precision/recall and latency so performance can be verified against the acceptance criteria. I’m ready to review the available dataset/vocabulary and define the first MVP milestone.

@namangarg820

From the beginning, my professional journey has been about finding smart solutions for every client requirement, and this project resonates strongly with my passion for innovation. With 8 years in the industry and counting, I've built a solid foundation in various domains such as AI. As a result, I'm experienced in using and implementing computer-vision models including TensorFlow, PyTorch and MediaPipe to recognize and classify complex signs. Additionally, my expertise extends to creating responsive web interfaces like the one you've described. I understand that speed is crucial in making the tool effective and realistic, so I'm committed to delivering sub-second latency for both text generation and speech synthesis. As further evidence of my capability to meet these targets, I have delivered similar projects succesfully in the past. Finally, I pride myself on creating thoroughly documented and easily deployable codes that can be seamlessly integrated into different platforms — an essential quality given your plan for future expansion into mobile applications. In summary, my well-rounded comprehension of AI, along with a successful track record and strong commitment to client satisfaction makes me your ideal freelancer for this project. Let’s make your vision a reality!

@TechWagger2026

With more than 14 years of experience in web and mobile app development, I am confident that I can fulfill your ambitious project for an AI-powered ASL chatbot. Tailored to your specific requirements, I promise to deliver a product that not only meets your scope of work but also exceeds your expectations. To address your concerns about latency and seamless interaction, I will leverage my experience working on LAMP architecture along with cloud hosting platforms like AWS and Azure to provide you with a blazing fast web application. Additionally, being well versed in third-party integrations, I can seamlessly integrate APIs for smooth functionality with browsers like Chrome, Edge, and Firefox without requiring extra plugins. In conclusion, I am well-equipped to tackle this project from all angles – as a skilled full-stack developer with a strong emphasis on MERN/MEAN stacks for the frontend and clear proficiency in computer vision applications; with users’ experience at the forefront through smooth and responsive interfaces while keeping a strong eye on performance and latency to make sure the interaction feels natural as it should. My mission is to help businesses scale and thrive with robust, modern, and efficient technology solutions, which makes me the ideal candidate for this project. Let’s build together!

@rohank2502

You want a browser tool where someone signs to the camera, sees the words appear, and hears them spoken so practice with hearing people feels natural. I can start right now. In 24 to 48 hours you get a live sample: camera on, signs as text, text spoken out loud in a normal desktop browser. The hard part is accuracy and speed on the alphabet plus everyday words in normal lighting. I will prove that first, then wrap it in a simple page. Full code, a short setup note, and a demo video. Which everyday signs should sit next to the alphabet in that first sample?

@iterativeTech

As an AI & Cloud Data Engineering Specialist, I have the extensive experience necessary to build the high-quality ASL chatbot you seek. My work is focused on driving real, tangible outcomes through technology which I believe uniquely qualifies me for this project. Having delivered intelligent systems that improve operational efficiency and reduce costs, all while enhancing customer experience - I bring a business-first mindset to technical challenges.I have profound knowledge in similar tools like MediaPipe, TensorFlow, PyTorch, GPT models and many more. Drawing from my expertise across finance, healthcare and enterprise environments,I excel at transforming data into measurable insights aligning them with business objectives.I can offer significant advantages while building an ASL model that has a 90%+ accuracy even in normal indoor lighting and keeps latency low. Not only am I committed to deploying a scalable, production-ready system but also providing clean, well-commented code with brief deployment instructions and even a demo video showcasing the system working on a standard desktop browser.

@priyanshuk879

Hi, I can build this ASL recognition system as a modular browser-based application covering the complete flow from webcam input to sign recognition, text conversion and natural speech output. I can work with Python, MediaPipe, TensorFlow or PyTorch for the computer-vision pipeline and optimize the inference flow to keep latency low enough for conversational interaction. The web interface can provide live camera input, recognized text and immediate speech output while remaining compatible with Chrome, Edge and Firefox without requiring plugins. I can also structure the project for Docker-based deployment on your Ubuntu VPS and provide clean source code, documentation and a working demo. I understand that the 90% accuracy target and sub-second response requirement will depend heavily on the dataset, lighting and vocabulary, so I would establish a baseline first and then improve recognition through preprocessing, model tuning and testing against your acceptance criteria. Thanks!

@Anika1802

Hello, I can build an AI-powered web chatbot that recognises ASL signs through a webcam, converts them into text, and produces natural speech in real time, with a clean and user-friendly interface. With 10+ years of experience in web development, Python, AI/ML, computer vision, TensorFlow/PyTorch, and API integrations, I can handle the complete solution including ASL detection, sign classification, live transcription, text-to-speech, responsive UI, and low-latency optimisation. I’ll keep the architecture modular and well documented so future features such as mobile apps, expanded vocabulary, and additional sign languages can be added easily. The delivery will include clean source code, Docker setup, VPS deployment documentation, browser testing, and a working demo. Let’s connect to discuss the ASL dataset, vocabulary, model approach, and development milestones. Thank you Regards Vandini

@sugamkumar27

Hello, I can develop the ASL sign-to-speech web application with real-time webcam recognition, text conversion, and natural voice output. I can use Python with MediaPipe/TensorFlow or PyTorch for sign recognition and build a responsive browser-based interface that works across Chrome, Edge, and Firefox. The system can be structured modularly so additional signs, languages, and mobile support can be added later. I will also provide clean source code, deployment instructions, and a working demo for testing. I can start immediately. Best regards, Sugam

@bojans9

Hi, I can build your AI-powered ASL Sign-to-Text-to-Speech web application with real-time webcam recognition, live text transcription, and natural speech output. My approach would use MediaPipe + TensorFlow/PyTorch, with a responsive browser interface designed for low-latency performance. The system will be modular and scalable for future vocabulary, mobile apps, and additional sign languages. I can deliver clean source code, Docker deployment for Ubuntu VPS, documentation, and a working demo. I will also focus on achieving your 90%+ accuracy and sub-second response targets through proper model testing and optimization. I’d be happy to discuss the ASL vocabulary and dataset scope before providing the final timeline and milestone plan

@shaun4014

Hello, ➤ I understand you’re looking for a reliable professional to develop an AI-powered web chatbot for real-time ASL recognition and speech synthesis. This project is both innovative and impactful, aiming to enhance communication for the deaf and non-verbal community. ✦ PROFESSIONAL QUALITY | FAST COMMUNICATION | UNLIMITED REVISIONS ✦ ❇️ WHAT I CAN OFFER: ▪ Expertise in building and fine-tuning computer-vision models using TensorFlow and MediaPipe for accurate ASL detection. ▪ Development of a responsive web interface that ensures seamless interaction with low latency. ▪ Clear, well-commented source code along with a comprehensive deployment guide to facilitate easy setup on your VPS. ▪ Regular updates and open communication to align with your vision and project goals. ▪ A demo video showcasing the system's functionality in a standard browser environment. ❇️ MY APPROACH: I prioritize understanding your needs and delivering a robust, user-friendly solution. With experience in gesture recognition and browser-based applications, I am well-equipped to bring your vision to life. ✨ I’m ready to get started and can begin immediately. Send me the details, and I’ll ensure the project is handled professionally from start to finish. Regards, Shaun Kelly

@digitaldotsent

Hi there, I read your post on "ASL Chatbot: Sign to Speech" and this is squarely what I do — RAG chatbots that answer accurately from your own documents, not generic replies. How I'd approach it: • Map the exact flow you need and confirm scope with you first (no guessing) • Build it with a working demo you can test before final delivery • Clean handover — you keep control of any API keys/accounts, no lock-in I run my own company on this exact stack (AI chatbots, n8n/Make automations, CRM integrations), so this is my day-to-day work, not an experiment. Fixed scope, fixed price, honest timelines. One quick question to scope it properly: Roughly how many documents/pages should the bot draw answers from? Happy to share relevant examples. Looking forward to it, Digital Dots