Lingvo is a TensorFlow based framework focused on building and training sequence models, especially for language and speech tasks. It was originally developed for internal research and later open sourced to support reproducible experiments and shared model implementations. The framework provides a structured way to define models, input pipelines, and training configurations using a common interface for layers, which encourages reuse across different tasks. It has been used to implement state of the art architectures such as recurrent neural networks, Transformer models, variational autoencoder hybrids, and multi task systems. Lingvo includes reference models and configurations for domains like machine translation, automatic speech recognition, language modeling, image understanding, and 3D object detection. Centralized hyperparameter configuration files allow researchers to share exact experiment setups so others can retrain and compare results reliably.
Features
- Framework centered on sequence models for language and speech tasks
- Shared layer interface that promotes code reuse across many model types
- Reference configs and models for translation, ASR, language modeling, and vision
- Optimized input pipelines and fast distributed training support
- Centralized hyperparameter management for reproducible experiments
- Tools and patterns for exporting models to serving and mobile environments