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An application that aims to produce the transcripts of a meeting. Apart from the transcripts, it incorporates an in-built Voice Classification Software, capable of identifying and distinguishing between each participant, thus personalizing the transcripts with respect to each participant
A multi-modal AI system that detects whether images, audio, or text are real or AI-generated. Built using CNNs, NLP, and audio feature extraction with a unified Streamlit interface for real-time authenticity verification.
Streamliner-AI is a fully automated, asynchronous Python pipeline designed to monitor Kick streamers, detect viral high-energy moments, generate vertical clips optimized for social media, and publish them to TikTok without manual intervention.
Demonstration for the Qwen/Qwen3-TTS-12Hz models using Daggr for modular UI nodes. Supports voice design (prompt-to-speech), voice cloning (zero-shot), and custom voice synthesis with multiple speakers and languages. Features lazy model loading to optimize memory, multi-model sizes (0.6B and 1.7B), ASR and support for various audio inputs.
A Python-based digital audio signal filtering project using Butterworth low-pass filters. Loads a .wav file, applies noise reduction by filtering out high-frequency components, and visualizes the frequency response. Built with NumPy, SciPy, Matplotlib, and SoundFile.
Voice Assistant powered by LangChain and OpenAI Whisper. Features real-time speech recognition, multi-LLM support (OpenAI, Google), and computer vision capabilities via OpenCV. Enables natural voice interactions with advanced AI responses.
Telegram Bot that can: 1) Preprocess and save audio messages from dialogues to a SQLite DB, 2) Determine if there are faces on sent photos and store them in that case.
This case study uses Multimodal Generative AI (text, image, audio, video) to create a complete, professional digital marketing campaign for the small bakery, demonstrating a cost-effective content creation process.