There are several open source speech-to-text libraries available that you can consider, depending on your requirements and programming language preference. Here are a few suggestions:

1. Mozilla DeepSpeech: A popular open source speech recognition engine developed by Mozilla. It is written in Python and can be used to transcribe audio files or perform real-time speech recognition.

2. Kaldi: A toolkit for speech recognition that supports several languages and acoustic models. It is written in C++ and has a modular design, making it easy to customize and extend.

3. Google Cloud Speech-to-Text: Google provides a cloud-based speech recognition API that can be used to transcribe audio files or perform real-time speech recognition. While the API is not open source, it provides a free tier for testing and development purposes.

4. CMUSphinx: An open source toolkit for speech recognition that supports several languages and acoustic models. It is written in C and can be used to transcribe audio files or perform real-time speech recognition.

5. Jasper: An open source platform for developing voice-controlled applications. It is written in Python and includes a speech recognition engine based on the PocketSphinx library.

6. Pocketsphinx: A lightweight speech recognition engine developed by Carnegie Mellon University. It is written in C and can be used for offline speech recognition on resource-constrained devices.

These are just a few of the many open source speech-to-text libraries available. You should evaluate each library based on your requirements, available resources, and programming language preference.
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