Thonburian Whisper is a Thai Automatic Speech Recognition (ASR) model fine-tuned from OpenAI's Whisper, provided as a reusable application with associated tools. The repository offers the pre-trained model hosted on Hugging Face, along with utilities for transcription, long-form audio processing, TensorRT conversion, and evaluation. Key components include a CLI tool for long-form transcription using VAD and syllable segmentation, scripts for converting the model to TensorRT format for efficient inference, and evaluation metrics calculation. The architecture consists of modular Python scripts and notebooks that demonstrate usage rather than a monolithic application, with clear separation between model usage, audio preprocessing, and post-processing.
FireRedASR is an open-source industrial-grade automatic speech recognition (ASR) system supporting Mandarin, Chinese dialects, and English. It provides two model variants: FireRedASR-AED (Attention-based Encoder-Decoder with Conformer encoder and Transformer decoder) and FireRedASR-LLM (Encoder-Adapter-LLM framework leveraging Qwen2-7B). The codebase includes a CLI tool (`speech2text.py`), a Python API (`FireRedAsr`), feature extraction (fbank with CMVN), tokenization (mixed Chinese/English SentencePiece), and utilities for WER computation. It also includes a complete Triton Inference Server deployment with TensorRT-LLM acceleration for the AED model, with Docker support and benchmarking scripts. The architecture is modular: data preprocessing, model definitions, tokenizers, and inference orchestration are cleanly separated, though the model components are tightly coupled to the specific architectures. The repository is actively maintained with recent commits and demonstrates strong engineering craftsmanship in both the core ASR implementation and the production-grade deployment stack.
Parakeet.cpp is a high-performance speech recognition inference library for NVIDIA's Parakeet model family (TDT-CTC, RNNT, Streaming EOU, Nemotron, Sortformer), written in C++ with C bindings. It provides offline and streaming transcription, speaker diarization, voice activity detection (VAD), beam search with optional n-gram language model fusion, phrase boosting, and timestamp extraction. The library is built on the axiom tensor library with Metal GPU acceleration for Apple Silicon, and supports audio input from WAV, FLAC, MP3, and OGG formats. The codebase includes a CLI tool, a Unix domain socket server example, and a rich set of examples covering all major features. While primarily an application/library for production ASR inference, it also contains research-oriented model conversion scripts (NeMo to safetensors) and a benchmark script comparing with PyTorch inference, giving it a hybrid character. The architecture is cleanly modular, with separate modules for audio I/O, VAD, model encoders/decoders, and decoding algorithms. The C API enables binding to Python, Swift, Rust, and other languages. Documentation and build system are well-maintained, and the repository is actively developed with recent commits.