Twitch Streamer GPT is a NodeJS-based Twitch enhancement tool, offering interactive stream experiences with AI-powered automated responses, voice command activations, and advanced modules. It's easy to set up and suited for users of all tech levels.

ProctoAI-Automated Exam Proctoring System Developed an Automated Exam Proctoring System (AEPS) utilizing AI-based algorithms for online exams. Achieved candidate verification, mobile phone detection, voice recognition, and secure exam environment. Used React.js, Redux, Node.js, and TensorFlow.js in the tech stack.

Automated video tagging system that uses AI/ML to generate relevant tags based on the voice path of a video.

AI-powered book authoring platform that guides writers from concept to draft through interactive interviews, voice/text input, and intelligent content generation. Features rich text editing, automated table of contents, Q&A-based development, and PDF/DOCX export.

Audio classification or sound classification can be referred to as the process of analyzing audio recordings. This amazing technique has multiple applications in the field of AI and data science such as chatbots, automated voice translators, virtual assistants, music genre identification, and text to speech applications. In this case we are classifying the given dataset consisting of 6500 speech files into the corresponding emotions portrayed and their levels. We will be implementing Audio classification by using the TensorFlow machine learning framework. We would be considering a raw audio dataset and categorize it based on the two 􏰜􏰕􏰟􏰆􏰜􏰏 􏰠􏰡􏰆􏰏􏰢􏰓 􏰕􏰑􏰖 􏰠􏰡􏰆􏰏􏰣􏰓. Followed by pre-processing, creating, and training a deep learning model to perform classification. We convert the audio signal from raw audio into two spectrograms before being fed into the models. A spectrogram is a visual way of representing the signal strength of a signal over time at various frequencies present in a particular waveform.

A Python-based tool for automated podcast processing and summarization using speaker diarization and AI voice synthesis.

Voice AI HR Agent – An AI-powered voice system for automated candidate screening. It conducts phone interviews, transcribes responses, analyzes sentiment, extracts key skills, and provides structured hiring recommendations.

CHAT-TWILIO-API is an innovative voice-based application leveraging Twilio Voice and Gemini AI to deliver seamless, intelligent, and human-like voice interactions for customer service and automated assistance.

A Golang application that integrates Twilio Voice with OpenAI's language models. This project enables voice interactions powered by AI, allowing for intelligent phone call handling, voice-based chatbots, or automated customer service systems.

A Python-based project that combines AI models and voice assistant technology to streamline student management tasks, such as maintaining records, tracking performance, and providing automated responses or actions through voice commands.

RecruitAI is an AI-powered hiring co-pilot that streamlines the entire recruitment process — from generating job descriptions to shortlisting candidates and sending offer letters. Built using Next.js, n8n, PostgreSQL, and OmniDimension Voice AI, it integrates voice/text input, real-time scheduling, AI-based ranking, and automated onboarding to make

“An AI-powered mock interview and assessment platform with resume analysis, real-time voice-based interviews, speech-to-text, automated feedback, and proctoring using face detection to ensure interview integrity.”

A fully automated voice-based single page web-application that delivers the latest news. The app is designed using react, and material-UI. The backend is integrated with Alan AI to provide voice-control functionality which enables it to respond to voice input from the user as well as have a casual conversation with the client.

This repository contains the backend code for the Farmer Call Center application, an AI-based voice-assisted contact center designed to assist farmers with their problems. Farmers can log their problems through phone calls, SMS, or the website, and in return, an automated voice response provides them with the most appropriate solutions.

In this project we implement a biometric attendance system that scans for fingerprints to record and store attendance data with the date and time of entry. It is also used as a security system that allows access to authorized people only. To improve the quality of life of the user, custom automated voice messages are used to welcome or guide the user through the process. We use the fingerprint module to scan or input the fingerprint templates of the user. After storing their fingerprint, the users can now use it to gain access into their place of work where the system will record the date and time of entry of the person. Along with this, a speaker is used to give voice messages. Audio encoding software such as audacity is used to convert AI based MP3 audio file to convert into 16-bit PCM. This can be utilized with help of PCM library on Arduino IDE. With the use of 4 buttons; ENROLL, OK/DEL, UP and DOWN users can navigate their way around this simple but cost- effective system. Administrator can view, delete the attendance log at any point of time. With a EEPROM of 1 KB, we can store 7 bytes of date and time data for 4 different users up to 30 entries at any given time. With increased memory, higher number of people can be enrolled.

AI-powered voice support system that enables real-time voice-based interaction using speech recognition and text-to-speech for automated user assistance.

AI-powered mock interview platform with voice-based agentic behavior, real-time interview generation, Firebase backend, and automated AI feedback. Submission for Eightfold.ai Agentic Interview Partner assignment.

A Python-based Virtual Assistant named Jarvis. Features voice recognition, automated web browsing, music playback, and AI-powered responses using Cohere API.

A desktop-based AI-powered Smart Assistant built with Python and Eel, designed to perform automated tasks, respond to voice commands, and integrate with a modern web interface.

AI-powered voice-based interview platform that conducts automated technical interviews, evaluates responses using LLMs, and provides real-time feedback. Built with Spring Boot, React, Python, and Google Gemini.

This application showcases an AI-powered voice-based agent designed for qualitative interviews and survey data collection. It leverages advanced AI techniques to conduct dynamic and engaging interviews, demonstrating the potential for AI in automated data collection and analysis.

AI Voice Assistant (Vapi + Exotel) is a production-ready Next.js project that integrates Vapi AI and Exotel telephony to build a multilingual voice call center assistant. It enables both web-based and phone interactions, supporting automated outbound and inbound calls, lead capture, and customer service workflows in multiple languages.

Automated Music Playing System Using Emotion Detection This project is an AI-powered music player that detects emotions from voice inputs and plays music based on the user's mood. It integrates voice recognition, speech emotion analysis, and machine learning to classify emotions in real-time and generate mood-based playlists.

ProctoAI-Automated Exam Proctoring System Developed an Automated Exam Proctoring System (AEPS) utilizing AI-based algorithms for online exams. Achieved candidate verification, mobile phone detection, voice recognition, and secure exam environment. Used React.js, Redux, Node.js, and TensorFlow.js in the tech stack.

AI-based voice-assisted Contact Center for assisting Farmers for their problems. Farmers can log their problems with the contact center thru phone calls / SMS / website and in return an automated voice response can be provided to the farmers with a most appropriate solution for their problems.

A modular Python-based AI Voice Assistant (Jarvis-inspired). Features integrated Speech-to-Text (STT), custom Text-to-Speech (TTS) functions, and automated task handling. Built with a dedicated UI and brain module for intelligent response generation.

Aryan AI: Voice-Automated Personal Assistant A modular Python-based assistant designed for hands-free desktop control. It leverages SpeechRecognition and pyttsx3 to execute commands including automated web navigation, YouTube playback, and real-time typing. Built with robust error handling and time-aware logic to streamline daily productivity.

This project is an end-to-end AI automation pipeline for HR teams. It processes uploaded resumes, extracts structured details, performs ATS scoring, auto-shortlists eligible candidates, moves shortlisted resumes to a separate GCS folder, triggers automated email invitations, and conducts a voice-based AI interview using Gemini + TTS/STT.

Built a full-stack AI interview platform using Next.js 15, React 19, TypeScript, and FastAPI. Integrated LangChain with Gemini 2.5 Pro for resume-based question generation, added cross-browser voice recognition with fallback logic, and implemented secure auth via NextAuth, Prisma, and PostgreSQL. Automated screening reduced recruiter workload by 60

ApplyOS is an open-source, AI-powered career platform designed to help you land your dream job. It goes beyond simple tracking—offering intelligent resume analysis, automated cover letter generation, and realistic voice-based interview practice. Built with Next.js, Supabase, and Gemini 2.5/3.0, it serves as your personal career copilot.