Lingtrain Aligner — ML powered library for the accurate texts alignment.

Related tags

Text Data & NLPlingtrain-aligner
Overview

Lingtrain Aligner

ML powered library for the accurate texts alignment in different languages.

Cover

Purpose

Main purpose of this alignment tool is to build parallel corpora using two or more raw texts in different languages. Texts should contain the same information (i.e., one text should be a translated analog oh the other text). E.g., it can be the Drei Kameraden by Remarque in German and the Three Comrades — it's translation into English.

Process

There are plenty of obstacles during the alignment process:

  • The translator could translate several sentences as one.
  • The translator could translate one sentence as many.
  • There are some service marks in the text
    • Page numbers
    • Chapters and other section headings
    • Author and title information
    • Notes

While service marks can be handled manually (the tool helps to detect them), the translation conflicts should be handled more carefully.

Lingtrain Aligner tool will do almost all alignment work for you. It matches the sentence pairs automatically using the multilingual machine learning models. Then it searches for the alignment conflicts and resolves them. As output you will have the parallel corpora either as two distinct plain text files or as the merged corpora in widely used TMX format.

Supported languages and models

Automated alignment process relies on the sentence embeddings models. Embeddings are multidimensional vectors of a special kind which are used to calculate a distance between the sentences. Supported languages list depend on the selected backend model.

  • distiluse-base-multilingual-cased-v2
    • more reliable and fast
    • moderate weights size — 500MB
    • supports 50+ languages
    • full list of supported languages can be found in this paper
  • LaBSE (Language-agnostic BERT Sentence Embedding)
    • can be used for rare languages
    • pretty heavy weights — 1.8GB
    • supports 100+ languages
    • full list of supported languages can be found here

Profit

  • Parallel corpora by itself can used as the resource for machine translation models or for linguistic researches.
  • My personal goal of this project is to help people building parallel translated books for the foreign language learning.
You might also like...
Sentence boundary disambiguation tool for Japanese texts (日本語文境界判定器)

Bunkai Bunkai is a sentence boundary (SB) disambiguation tool for Japanese texts. Quick Start $ pip install bunkai $ echo -e '宿を予約しました♪!まだ2ヶ月も先だけど。早すぎ

Megagon Labs 160 Dec 23, 2022
Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

Code for EMNLP'21 paper "Types of Out-of-Distribution Texts and How to Detect Them"

Udit Arora 19 Oct 28, 2022
Neural text generators like the GPT models promise a general-purpose means of manipulating texts.

Boolean Prompting for Neural Text Generators Neural text generators like the GPT models promise a general-purpose means of manipulating texts. These m

Jeffrey M. Binder 20 Jan 9, 2023
Biterm Topic Model (BTM): modeling topics in short texts
Biterm Topic Model (BTM): modeling topics in short texts

Biterm Topic Model Bitermplus implements Biterm topic model for short texts introduced by Xiaohui Yan, Jiafeng Guo, Yanyan Lan, and Xueqi Cheng. Actua

Maksim Terpilowski 49 Dec 30, 2022
This repository contains Python scripts for extracting linguistic features from Filipino texts.

Filipino Text Linguistic Feature Extractors This repository contains scripts for extracting linguistic features from Filipino texts. The scripts were

Joseph Imperial 1 Oct 5, 2021
Text Classification in Turkish Texts with Bert
Text Classification in Turkish Texts with Bert

You can watch the details of the project on my youtube channel Project Interface Project Second Interface Goal= Correctly guessing the classification

null 42 Dec 31, 2022
Code for our paper
Code for our paper "Mask-Align: Self-Supervised Neural Word Alignment" in ACL 2021

Mask-Align: Self-Supervised Neural Word Alignment This is the implementation of our work Mask-Align: Self-Supervised Neural Word Alignment. @inproceed

THUNLP-MT 46 Dec 15, 2022
A pytorch implementation of the ACL2019 paper
A pytorch implementation of the ACL2019 paper "Simple and Effective Text Matching with Richer Alignment Features".

RE2 This is a pytorch implementation of the ACL 2019 paper "Simple and Effective Text Matching with Richer Alignment Features". The original Tensorflo

null 286 Jan 2, 2023
Tensorflow Implementation of A Generative Flow for Text-to-Speech via Monotonic Alignment Search

Tensorflow Implementation of A Generative Flow for Text-to-Speech via Monotonic Alignment Search

Ankur Dhuriya 10 Oct 13, 2022
Comments
  • File Already Exists

    File Already Exists

    Делаю docker pull lingtrain/aligner:v4 Загружаю текстовый файл и...

    image

    После вот такого предупреждения ничего не происходит Причём оно вылазит на любой текстовый файл

    opened by puffofsmoke 1
  • Fix XML creation:

    Fix XML creation:

    • prevent parent tag duplication for (langs, author, title)
    • add tags for tmx export
    • use 'direction' for splitting paragraphs
    • do not use bs4 (generates incorrect xml), change to lxml
    opened by BorisNA 0
  • A error when I use “splitter.split_by_sentences_wrapper”，please help check the error

    A error when I use “splitter.split_by_sentences_wrapper”，please help check the error

    when I use “splitted_from = splitter.split_by_sentences_wrapper(text1_prepared, lang_from)” return list，

    But I see that there will be a conflict when insert sqlite ，specific error：

    File "ling_test.py", line 36, in aligner.fill_db(db_path, splitted_from, splitted_to) File "lingtrain_aligner/aligner.py", line 498, in fill_db db.executemany("insert into languages(key, val) values(?,?)", [("from", lang_from), ("to", lang_to)]) sqlite3.InterfaceError: Error binding parameter 1 - probably unsupported type.

    opened by Amen-bang 5
  • Add text splitting into small parts

    Add text splitting into small parts

    The current version ignores the H1-H5 headers that were added by user. But when book was translate text from chapter 1 will be translate as a chapter 1 text into another language. You can use this fact and split a big text to small parts.

    Next idea - try split a big text to small blocks automatically: Select a few sentences from original text(for example 10 sentences) and using loop try to find translate block in the thanslated text.

    You can use the next psedocode:

    left_array = original_sentences[100:110]
sum=[]
for i=50;i<150 do:
   right_array_candidate=translated_sentences[i:i+10]
   sum[i]=sum(cosunuse_distance(left_array,right_array_candidate))

rigth_array=get_index_with_max_value(sum)

left_text_split_index=left_array[0]
rigth_text_split_index=rigth_array[0]
    opened by AigizK 0
Releases(0.1.0)
Owner
Sergei Averkiev
Software Engineer. Eager to learn languages and machine learning approaches. Live in Moscow.
Sergei Averkiev
GitHub Repository
Code Generation using a large neural network called GPT-J

CodeGenX is a Code Generation system powered by Artificial Intelligence! It is delivered to you in the form of a Visual Studio Code Extension and is Free and Open-source!

DeepGenX 389 Dec 31, 2022
This repository is home to the Optimus data transformation plugins for various data processing needs.

Transformers Optimus's transformation plugins are implementations of Task and Hook interfaces that allows execution of arbitrary jobs in optimus. To i

Open Data Platform 37 Dec 14, 2022
Simple multilingual lemmatizer for Python, especially useful for speed and efficiency

Simplemma: a simple multilingual lemmatizer for Python Purpose Lemmatization is the process of grouping together the inflected forms of a word so they

Adrien Barbaresi 70 Dec 29, 2022
NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking

pretrain4ir_tutorial NLPIR tutorial: pretrain for IR. pre-train on raw textual corpus, fine-tune on MS MARCO Document Ranking 用作NLPIR实验室, Pre-training

ZYMa 12 Apr 07, 2022
A curated list of efficient attention modules

awesome-fast-attention A curated list of efficient attention modules

Sepehr Sameni 891 Dec 22, 2022
Applying "Load What You Need: Smaller Versions of Multilingual BERT" to LaBSE

smaller-LaBSE LaBSE(Language-agnostic BERT Sentence Embedding) is a very good method to get sentence embeddings across languages. But it is hard to fi

Jeong Ukjae 13 Sep 02, 2022
topic modeling on unstructured data in Space news articles retrieved from the Guardian (UK) newspaper using API

NLP Space News Topic Modeling Photos by nasa.gov (1, 2, 3, 4, 5) and extremetech.com Table of Contents Project Idea Data acquisition Primary data sour

edesz 1 Jan 03, 2022
A fast Text-to-Speech (TTS) model. Work well for English, Mandarin/Chinese, Japanese, Korean, Russian and Tibetan (so far). 快速语音合成模型，适用于英语、普通话/中文、日语、韩语、俄语和藏语（当前已测试）。

简体中文 | English 并行语音合成 [TOC] 新进展 2021/04/20 合并 wavegan 分支到 main 主分支，删除 wavegan 分支！ 2021/04/13 创建 encoder 分支用于开发语音风格迁移模块！ 2021/04/13 softdtw 分支 支持使用 Sof

Atomicoo 161 Dec 19, 2022
STT for TorchScript is a port of Coqui STT based on DeepSpeech to PyTorch.

st3 STT for TorchScript is a port of Coqui STT based on DeepSpeech to PyTorch. Currently it supports converting pbmm models to pt scripts with integra

Vlad Ki 8 Oct 18, 2021
The source code of HeCo

HeCo This repo is for source code of KDD 2021 paper "Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning". Paper Link: htt

Nian Liu 106 Dec 27, 2022
A python wrapper around the ZPar parser for English.

NOTE This project is no longer under active development since there are now really nice pure Python parsers such as Stanza and Spacy. The repository w

ETS 49 Sep 12, 2022
pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

The PyTorch-Kaldi Speech Recognition Toolkit PyTorch-Kaldi is an open-source repository for developing state-of-the-art DNN/HMM speech recognition sys

Mirco Ravanelli 2.3k Dec 27, 2022
Active learning for text classification in Python

Active Learning allows you to efficiently label training data in a small-data scenario.

Webis 375 Dec 28, 2022
Code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

This repository contains the code for the paper in Findings of EMNLP 2021: "EfficientBERT: Progressively Searching Multilayer Perceptron via Warm-up Knowledge Distillation".

Chenhe Dong 28 Nov 10, 2022
Multi-Scale Temporal Frequency Convolutional Network With Axial Attention for Speech Enhancement

MTFAA-Net Unofficial PyTorch implementation of Baidu's MTFAA-Net: "Multi-Scale Temporal Frequency Convolutional Network With Axial Attention for Speec

Shimin Zhang 87 Dec 19, 2022
Correctly generate plurals, ordinals, indefinite articles; convert numbers to words

NAME inflect.py - Correctly generate plurals, singular nouns, ordinals, indefinite articles; convert numbers to words. SYNOPSIS import inflect p = in

Jason R. Coombs 762 Dec 29, 2022
Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

gpt-2-simple A simple Python package that wraps existing model fine-tuning and generation scripts for OpenAI's GPT-2 text generation model (specifical

Max Woolf 3.1k Jan 07, 2023
SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering.

SEJE is a prototype for the paper Learning Text-Image Joint Embedding for Efficient Cross-Modal Retrieval with Deep Feature Engineering. Contents Inst

0 Oct 21, 2021
Natural Language Processing for Adverse Drug Reaction (ADR) Detection

Natural Language Processing for Adverse Drug Reaction (ADR) Detection This repo contains code from a project to identify ADRs in discharge summaries a

Medicines Optimisation Service - Austin Health 21 Aug 05, 2022
Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together

SpeechMix Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together. Introduction For the same input: from datas

Eric Lam 31 Nov 07, 2022