ASRT (Automatic Speech Recognition Toolkit) is a Chinese speech recognition system that provides both training and inference capabilities. It uses a deep CNN acoustic model with Connectionist Temporal Classification (CTC) and an N-gram language model based on a maximum entropy hidden Markov model. The system supports multiple backends (TensorFlow/Keras and experimental PyTorch) and can be trained on several Chinese speech corpora (THCHS30, ST-CMDS, etc.). It includes HTTP and gRPC servers for real-time inference, a speech recorder utility, and client libraries. The architecture is monolithic with separate scripts for training, evaluation, and serving. The codebase is functional but shows signs of technical drift, such as using deprecated Keras APIs (fit_generator) and hardcoded paths. The language model implementation is a notable highlight, offering a non-trivial statistical decoding approach. The repository is popular but has a single maintainer and a high number of open issues.