MockingBird

Detailed Introduction

MockingBird is an open-source voice cloning and real-time speech generation toolkit designed for research and engineering use. It aims to clone a target speaker’s voice from very short audio samples (e.g., 5 seconds) and synthesize arbitrary text in that voice. Implemented in PyTorch, MockingBird includes preprocessing, training, and inference components, a demo toolbox, and optional web server interfaces for quick experimentation and local deployment.

Main Features

• Fast cloning: build a speaker representation from short audio clips and produce synthetic speech in a similar timbre.
• Cross-platform and hardware tested: runs on Windows and Linux, with notes for running on Apple M1; tested with GPUs like Tesla T4 and GTX series.
• Tooling and demos: includes training scripts, a demo toolbox, and a web.py web server for remote invocation.
• Community-shared models and comparisons for quality evaluation.

Use Cases

• Voice cloning research and experiments to validate speaker modeling methods.
• Prototyping speech products or demos that require sample-specific voices.
• Educational projects for learning TTS pipelines, vocoders, and model training workflows.

Technical Features

• Modular PyTorch codebase with encoder, synthesizer, and vocoder components for easy replacement and extension.
• Options to reuse pretrained encoders/vocoders while training the synthesizer to reduce time-to-results.
• Platform-specific setup guides (including Rosetta-based workarounds for M1 macOS) and extensive README/Wiki documentation.