STT –> LLM –> TTS pipeline in C
For speech-to-text, large-language-model inference and text-to-speech I created three wrapper libraries in C/C++ (using Whisper.cpp, Llama.cpp and Piper). Follow the URL to see an example that shows how to use these libraries for a speech-to-text, LLM inference, text-to-speech pipeline. Windows and Linux are supported.
STT –> LLM –> TTS pipeline in C launched on September 17, 2025 with 11 votes, #1,008 of 8,160 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
In plain words
STT → LLM → TTS pipeline in C provides three wrapper libraries for speech-to-text, language model inference, and text-to-speech processing. Built with Whisper.cpp, Llama.cpp, and Piper, it enables developers to create voice-based applications by chaining these components together. The project includes example code demonstrating integration patterns and supports both Windows and Linux platforms, making it suitable for developers building conversational AI applications in C or C++.
written from the facts on this page · September 2026
From the sources
Pure C wrapper library to use llama.cpp with Linux and Windows as simple as possible. - mt_llm/stt_llm_tts-pipeline-example at main · RhinoDevel/mt_llm
pipeline in C, via mt_stt, mt_llm and mt_tts, which are C/C++ wrapper libraries for Whisper.cpp , Llama.cpp and Piper . The instructions are for Windows, but the code should work in Linux, too. Take a look at the makefiles of mt_stt , mt_tts and mt_llm for hints. Then update the example project by adding STT as described for mt_stt . Proceed by creating the LLM example with the instructions for mt_llm by using the same folder . Open x64 Native Tools Command Prompt for VS 2022from github.com
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