Code to train a custom time-domain autoencoder to dereverb audio
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Updated
Nov 30, 2023 - Python
Code to train a custom time-domain autoencoder to dereverb audio
Dual-model speech AI toolkit for speaker verification and speaker-aware diarization, with streaming inference, meeting analysis, long-audio monitoring, and speaker-bank integration.
Unified dual-teacher distillation (ReDimNet + ASSIST) into Wav2Vec2 for speaker verification and deepfake detection
Local MCP server + CLI turning YouTube & local audio into rich sonic signatures. Extracts BPM, section-by-section key, vocal presence, transient punch, and 512-dim CLAP vibe embeddings. Powered by Demucs stem separation & librosa. 100% private, offline-first, and GPU-accelerated with graceful CPU/HPSS degradation.
This repository consists of projects where GANs were used to work with audio data like music generator etc.
Real-time speech enhancement pipeline — custom-trained U-Net denoising model, ONNX inference, Overlap-Add synthesis, and virtual audio routing for Teams, Zoom, and DAW use. CPU-only, no cloud dependency.
Stable Audio LoRA Trainer of salty goodness
Engine identification using acoustic signal analysis and machine learning to classify 8 vehicle types. Audio signals are processed using FFT and feature extraction, and a multi-class model predicts vehicle categories based on their unique sound patterns.
Audio analysis in javascript/typescript
Edge-deployable keyword spotter: INT8-quantized DS-CNN on Google Speech Commands, exported to ONNX, with fp32 vs INT8 benchmarks, a live mic demo, and a C++ inference harness.
Key Features: Simple VAE architecture with encoder/decoder Synthetic music data generation for training Interactive training with progress tracking Music generation from latent space sampling Audio conversion and playback Downloadable audio files
Machine learning system for music genre classification using feature engineering, stratified evaluation, SVC/XGBoost modeling, and reproducible prediction export.
Audio file processing pipeline with GPT-4-powered error diagnosis — detects codec issues, sample rate mismatches, and corruption artefacts with automated remediation suggestions.
Neural TTS and voice-cloning application using XTTS/VITS. Supports 3–30 s reference audio for speaker adaptation, real-time pitch/speed control, and WAV/MP3 export.
AI-generated audio summarisation pipeline — Whisper transcription, LLM key-insight extraction, and structured spoken summaries with TTS playback and Streamlit interface.
Convert Meta's HTDemucs (Hybrid Transformer Demucs) to Apple Core ML. Real-valued STFT/ISTFT wrapper, manual MHA decomposition, pre-computed overlap-add. Includes Swift example.
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