Kaldi

Kaldi is primarily written in C++, which can be challenging for developers more familiar with higher-level languages like Python.

While Kaldi supports DNNs, LSTMs, and RNN-T models, integrating state-of-the-art architectures often requires significant customization and additional development effort.

Setting up the environment for Kaldi involves compiling C++ code and configuring multiple dependencies, which can be time-consuming and error-prone.

Kaldi is optimized for batch processing and research purposes rather than low-latency real-time speech recognition tasks, leading to potential performance issues in live scenarios.