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 # Bertalign
-word embedding-based bilingual sentence aligner
+Word Embedding-Based Bilingual Sentence Aligner
 
 ## Evaluation Corpus
 This section describes the procedure of creating the evaluation corpora: the manually aligned corpus (MAC) of Chinese-English literary texts and the Bible corpus aligned at the verse level.
 ### MAC
-Firstly, 5 chapters and their translations are sampled from each of the 6 novels included in MAC, obtaining a corpus of 30 bitexts. We then split the corpus into **MAC-Dev** and **MAC-Test** with the former containing 6 chapters and the latter 24 chapters.
+Firstly, 5 chapters and their translations are sampled from each of the 6 novels included in MAC, obtaining a corpus of 30 bitexts. We then split the corpus into MAC-Dev and MAC-Test with the former containing 6 chapters and the latter 24 chapters.
 
 The **MAC-Test** is saved in [corpus/mac/test](./corpus/mac/test)
 
-The sampling schemes for building **MAC-Test** can be found at [corpus/mac/test/meta_data.tsv](./corpus/mac/test/meta_data.tsv)
+The sampling schemes for building MAC-Test can be found at [meta_data.tsv](./corpus/mac/test/meta_data.tsv)
 
-There are 4 subdirectories in **MAC-Test**. The [split](/corpus/mac/test/split) directory contains the sentence-split source texts, target texts and the machine translations of source texts, which are required by **Bleualign** to perform automatic alignment.
+There are 4 subdirectories in MAC-Test.
 
-The inputs to **Hunalign** are saved in the [tok](/corpus/mac/test/tok) directory.
+The [split](./corpus/mac/test/split) directory contains the sentence-split source texts, target texts and the machine translations of source texts, which are required by *Bleualign* to perform automatic alignment.
 
-The emb directory is made up of the overlapping sentences and their embeddings for Vecalign and BertAlign.
+The inputs to *Hunalign* are saved in the [tok](./corpus/mac/test/tok) directory.
+
+The [emb](./corpus/mac/test/emb) directory is made up of the overlapping sentences and their embeddings for *Vecalign* and *BertAlign*.
+
+We use [Intertext](https://wanthalf.saga.cz/intertext) to perform the manual alignment for MAC and save the gold alignments in the [intertext](./corpus/mac/test/intertext) directory.
+
+In order to facilitate system evaluations, we delete the XML tags and save the clean gold alignment file with only sentence IDs in the [gold](./eval/mac/test/gold) directory
+
+### Bible
+The Bible corpus is located in [corpus/bible](./corpus/bible)
+
+The directory makeup is similar to MAC, except that there is no *intertext* directory for manual alignments.
+
+The gold alignments for the Bible corpus are generated automatically from the original verse-aligned Bible corpus and saved in [eval/bible/gold](./eval/bible/gold)
+
+In order to compare the sentence-based alignments returned by various aligners with the verse-based gold alignments, we put the verse ID for each sentence in the files *corpus/bible/en.verse* and *corpus/bible/zh.verse*, which are used to merge consecutive sentences in the output if they belong to the same verse.
+
+## System Comparisons
+All the experiments reported in the paper are conducted using [Google Colab](https://colab.research.google.com/)
+### Job File
+Before performing the automatic alignment, a job file is created for each aligner for batch processing. Each row in the job file represents an alignment task, which is made of three tab-separated file names for source, target and output text.
+
+The job files for MAC-Test and Bible are located in *eval/mac/test/job* and *eval/bible/job*
+
+### Sentence Embeddings
+Before embedding the source and target sentences, we use the following Python script to create the combinations of consecutive sentences:
+```
+# MAC-Test
+python utils/overlap.py -i corpus/mac/test/split -o corpus/mac/test/emb/en.overlap –l en –n 8
+python utils/overlap.py -i corpus/mac/test/split -o corpus/mac/test/emb/zh.overlap –l zh –n 8
+
+# Bible
+python utils/overlap.py -i corpus/bible/split -o corpus/bible/en.overlap –l en –n 5
+python utils/overlap.py -i corpus/bible/split -o corpus/bible/zh.overlap –l en –n 5
+```
+Use parameters -i to specify the input data directory and -o the output file path.
+
+All the file suffixes in the input directory should end with the corresponding language code, e.g. 001.en and 001.zh etc., and match up with the parameter -l.
+
+The parameter -n indicates the number of overlapping sentences, which is similar to word n-grams applied to sentences.
+
+We use [Sentence Transformers](https://github.com/UKPLab/sentence-transformers) to convert texts into embeddings.
+
+To install Sentence Transformers, just run:
+```
+pip install sentence-transformers
+```
+After the installation, we run the following Python script to embed the bitexts to be aligned:
+```
+# MAC-Test
+python utils/embed.py –i corpus/mac/test/emb/en.overlap –o corpus/mac/test/emb/en.overlap.emb
+python utils/embed.py –i corpus/mac/test/emb/zh.overlap –o corpus/mac/test/emb/zh.overlap.emb
+
+# Bible
+python utils/embed.py –i corpus/bible/emb/en.overlap –o corpus/bible/emb/en.overlap.emb
+python utils/embed.py –i corpus/bible/emb/zh.overlap –o corpus/bible/emb/zh.overlap.emb
+```
+The parameter -i indicates the file containing sentence combinations.
+
+We use the [tofile](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tofile.html) method provided by Python’s Numpy module to save the sentence embeddings in the file designated by -o.