🎧 Audio Engineer | 🤖 AI Audio Specialist | 🛠 Building tools for speech datasets and voice AI pipelines
I work at the intersection of audio engineering and artificial intelligence, focusing on speech datasets, audio quality evaluation, and voice AI systems.
Currently contributing to AI audio training and evaluation workflows while building tools for automated audio processing and dataset analysis.
- Speech dataset engineering
- Voice AI evaluation
- Audio quality detection
- Python-based audio processing
- Voice AI pipelines (STT → LLM → TTS)
- Audio Editing & Restoration
- Mixing & Mastering
- Audio Quality Analysis
- Artifact Detection
- iZotope RX
- Speech Dataset Preparation
- AI Audio Annotation
- Voice Model Evaluation
- Speech Quality Assessment
- Python
- FFmpeg
- Librosa
- NumPy
- Pydub
- Git & GitHub
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Audio Batch Cleaner
Automated pipeline to normalize, trim silence, and convert large audio datasets. -
Speech Dataset Analyzer
Tool for analyzing dataset quality (clipping, loudness, duration, silence). -
Audio Quality Detector
Script that detects clipping, noise issues, and corrupted files in speech datasets. -
Voice AI Pipeline Demo
Simple pipeline demonstrating speech → text → AI → speech workflow.
- Build tools for speech dataset processing
- Improve voice AI quality evaluation
- Contribute to AI audio infrastructure