pycorrector is a toolkit for text error correction. 文本纠错,实现了Kenlm,T5,MacBERT,ChatGLM3,Qwen2.5等模型应用在纠错场景,开箱即用。
kenlm 开源项目推荐(37 个)
kenlm 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 37 个仓库State-of-the-art (ranked #1 Aug 2022) German Speech Recognition in 284 lines of C++. This is a 100% private 100% offline 100% free CLI tool.
Training an n-gram based Language Model using KenLM toolkit for Deep Speech 2
CTC+Beam_Search+kenlm 是用于以汉字为声学模型建模单元的解码系统
A complete instruction for training a Persian spell checker and a language model based on SymSpell and KenLM, respectively using Wikipedia dataset.
Wave2vec 2.0 Recognize pipeline
Romanian Automatic Speech Recognition from the ROBIN project
Targoman SMT framework source code
Optical Character Recognition + Instance Segmentation for russian and english languages
ONNX speech pipeline library for ASR (diarization, VAD), and TTS
🎲 KenLM extension for spaCy 2.0.
A Java JNI wrapper for KenLM: Faster and Smaller Language Model Queries
Real-Time ASR with CNN-BiLSTM: End-to-End Live Streaming Using PyTorch Lightning⚡
A macOS IME with a floating candidate window for word completions, spell corrections, and next-word predictions powered by KenLM n-gram models.
Neural Grammatical Error Correction for Romanian using Transformer
INACTIVE - http://mzl.la/ghe-archive - Generate language models from OSCAR corpora
Create and adapt n-gram and JSGF language models, e.g. for Kaldi-ASR nnet3 chain models from Zamia-Speech
Developed an AI tool to automatically generate captions and transcripts for YouTube videos in 67 languages and can generate summarized texts in 133 languages.
Automatic Speech Recognition using Conformer with Speech Sentiment Analysis & Text Summarizer
Scripts to train a n-gram language models on Wikipedia articles
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/kenlm。
- 该话题在 GitHub 上共有 37 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 7387 Star,覆盖 7 种主要语言,数据更新于 2026-11-09。
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