This repository is a curated list of resources for the Kaldi speech recognition toolkit, aimed at users ranging from beginners to advanced practitioners. It provides links to tutorials, scripts, advanced techniques, production-ready examples, and foundational research papers, enabling users to effectively leverage and develop speech recognition systems with Kaldi.

How It Works

The repository functions as a comprehensive, community-driven index of external resources. It categorizes information to guide users through different aspects of Kaldi, from initial setup and understanding core concepts to implementing advanced features like speaker diarization and deploying production-ready systems. The inclusion of specific utility scripts and production examples highlights practical applications and efficient workflows within the Kaldi ecosystem.

Quick Start & Requirements

• Primary Install/Run: Not applicable, as this is a resource list, not a software package.
• Prerequisites: Access to the internet to view linked resources. Kaldi itself requires a Linux environment, C++ compiler, and potentially Python. Specific tutorials may have additional dependencies like GPUs, CUDA, or specific datasets.
• Setup Time: N/A.
• Links:
  • Kaldi Official Website: http://kaldi-asr.org/
  • Beginner's Guide: A Medium post (author's recommendation)
  • Kaldi for Dummies Tutorial: Official Kaldi documentation
  • DNN Training Tutorial: Josh Meyer's tutorial
  • Eleanor Chodroff Kaldi Tutorial: Link provided in README
  • Speaker Diarization with Kaldi: Link provided in README
  • Understanding Kaldi Recipe: Link provided in README
  • Kaldi-ONNX Project: XiaoMi's project
  • kaldi-gstreamer-server: Link provided in README
  • Kaldi pretrained models: Link provided in README

Highlighted Details

• Curated list of beginner-friendly tutorials, including a recommended Medium post and the official "Kaldi for Dummies" guide.
• Practical utility scripts for data augmentation (speed, volume, resampling), data combining, log summarization, and model fine-tuning.
• Examples of "production-ready" Kaldi implementations, such as online2-tcp-nnet3-decode-faster and kaldi-gstreamer-server, for real-time ASR.
• Resources for understanding the mathematical and theoretical underpinnings of Kaldi, including WFSTs, language modeling, and GMMs.
• Links to foundational research papers describing Kaldi's architecture and advanced techniques like TDNNs and LSTMs.

Maintenance & Community

• The repository encourages community contributions for adding more links and resources.
• Specific maintainer information or community channels (like Discord/Slack) are not detailed in the provided README.

Licensing & Compatibility

• The repository itself, being a list of links, does not have a software license.
• The linked resources and the Kaldi toolkit itself are subject to their respective licenses. Kaldi is generally permissive for research and development, but users should verify specific licenses for any included scripts or models, especially for commercial use.

Limitations & Caveats

• Some linked resources, particularly older tutorials or presentations, may contain information that is outdated due to Kaldi's active development.
• The effectiveness and setup complexity of linked production examples can vary significantly.
• The README does not provide direct download links for Kaldi or its dependencies, requiring users to navigate to the official Kaldi website.