test

langid/langid_datafilesfin_dev.tsv → correct/correct_datafiles/correct_dev.tsv

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langid/langid_datafilesdan_dev.tsv → correct/correct_datafiles/correct_test.tsv

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+size 2339422

langid/langid_datafileseng_dev.tsv → correct/correct_datafiles/correct_train.tsv

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correct/create_correct_dataset.py

@@ -0,0 +1,140 @@
+from datasets import load_dataset
+import random
+import argparse
+import csv
+import glob
+import pandas as pd
+from sklearn.model_selection import train_test_split
+
+
+def main(args):
+    trans_chars = ",.:;!"
+    
+    filelist = glob.glob('../langid/sentences/*.txt')
+
+    data = pd.DataFrame()
+
+    for tsvfile in filelist:
+        print(f"Processing {tsvfile}")
+        tmp = pd.read_csv(tsvfile, sep='\t',on_bad_lines='skip',engine='python',encoding='utf8')
+        if len(tmp.columns)==1:
+            tmp.insert(0,'id','')
+        
+        tmp.columns=['id','source']   
+        data=pd.concat([data,tmp])
+
+   
+    # Trim
+    data['source'] = data['source'].str.strip()
+    
+    # Drop rows that does not end with punctation
+    data = data[data['source'].str[-1:].isin([".",",",":",";","!"])]
+    
+    # For not creating chaos later with . . . Just remove examples with elipsis 
+    data = data[~data['source'].str.contains("...", regex=False)] 
+    data = data[~data['source'].str.contains(". . .", regex=False)]
+   
+    #Drop the id
+    data = data.drop(['id'],axis=1)
+    
+    # Duplicate column
+    data['target'] = data['source']
+   
+    # Apply each method to 10% of the corpus
+    # set a stop
+    stop =int(len(data)/10)
+    stop_small = int(stop/2)
+
+    #Main shuffling
+    data = data.sample(frac=1).reset_index(drop=True)
+    
+    # Lowercase in 10% of the cases
+    data.loc[:stop,'source'] = data['source'].str.lower()
+    print(f"Lower casing 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+
+    # Uppercase in 5% of the cases
+    data.loc[:stop_small,'source'] = data['source'].str.upper()
+    print(f"Upper casing 5% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+
+
+    # Remove all spaces in 10% of the cases
+    data.loc[:stop,'source'] = data['source'].str.replace(" ","")
+    print(f"Removing space 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+
+    # Remove both spaces and do lowercasing in 10%
+    data.loc[:stop,'source'] = data['source'].str.replace(" ","")
+    data.loc[:stop,'source'] = data['source'].str.lower()
+    print(f"Removing space and doing lovercase 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+    
+    # Remove a random number of spaces in 10% of the cases
+    for index, row in data[0:stop].iterrows():
+        source = row['source']
+        #Find the spaces
+        spacepos = [pos for pos, char in enumerate(source) if char == " "]
+        random.shuffle(spacepos)
+        
+        #Reduce to a random number
+        spacepos = spacepos[0:random.randint(0,len(spacepos))]
+        
+        ##Sort in reverse order
+        spacepos.sort(reverse=True)
+        
+        ##Loop and replace
+        for s in spacepos:
+            source = source[:s] + source[s+1:]
+
+        data.loc[index,'source'] = source
+    
+    print(f"Removing a random number of spaces 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+
+    # Remove all punctation in 10% of the cases
+    trans_table = source.maketrans("", "", trans_chars)
+    data.loc[:stop,'source'] = data['source'].str.translate(trans_table)
+    print(f"Removing punctation 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+    
+    # Remove a random number of commas in 10% of the cases
+    for index, row in data[0:stop].iterrows():
+        source = row['source']
+        #Find the spaces
+        spacepos = [pos for pos, char in enumerate(source) if char == ", "]
+        random.shuffle(spacepos)
+
+        #Reduce to a random number
+        spacepos = spacepos[0:random.randint(0,len(spacepos))]
+
+        ##Sort in reverse order
+        spacepos.sort(reverse=True)
+
+        ##Loop and replace
+        for s in spacepos:
+            source = source[:s] + " " +source[s+1:]
+
+        data.loc[index,'source'] = source
+
+    print(f"Removing a random number of commas 10% - '{data.loc[0]['target']}' -> '{data.loc[0]['source']}'")
+    data = data.sample(frac=1).reset_index(drop=True)
+
+    # Train - test - dev
+    train, test = train_test_split(data, test_size=0.2)
+    test, dev = train_test_split(test, test_size=0.5)
+    
+    # Write the datasets to disk
+    train.to_csv('correct_datafiles/correct_train.tsv', index=False, header=False, sep='\t')
+    test.to_csv('correct_datafiles/correct_test.tsv', index=False, header=False, sep='\t')
+    dev.to_csv('correct_datafiles/correct_dev.tsv', index=False, header=False, sep='\t')
+
+def parse_args():
+    # Parse commandline
+    parser = argparse.ArgumentParser()
+    args = parser.parse_args()
+    return args
+
+if __name__ == "__main__":
+    args = parse_args()
+    main(args)

create_dataset_from_tsv.py → create_training_files.py

@@ -5,7 +5,7 @@ import glob
 import sys
 import os
 
-filelist = glob.glob('tsv_source_target/*.tsv')
+filelist = glob.glob('translate_dataset/*.tsv')
 
 data = pd.DataFrame()
 

langid/create_langid_trainset.py

@@ -32,7 +32,7 @@ for tsvfile in filelist:
     # Write the datasets to disk
     train.to_csv('langid_datafiles/'+lang+'_train.tsv', index=False, header=False, sep='\t')
     test.to_csv('langid_datafiles/'+lang+'_test.tsv', index=False, header=False, sep='\t')
-    dev.to_csv('langid_datafiles'+lang+'_dev.tsv', index=False, header=False, sep='\t')
+    dev.to_csv('langid_datafiles/'+lang+'_dev.tsv', index=False, header=False, sep='\t')
 
 
 print("Finished")

langid/langid_datafilesfao_dev.tsv

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langid/langid_datafilesisl_dev.tsv

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langid/langid_datafilesnno_dev.tsv

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langid/langid_datafilesnob_dev.tsv

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langid/langid_datafilessma_dev.tsv

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langid/langid_datafilessme_dev.tsv

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langid/langid_datafilessmj_dev.tsv

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langid/langid_datafilessmn_dev.tsv

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langid/langid_datafilessms_dev.tsv

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langid/langid_datafilesswe_dev.tsv

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tsv_all_source_target/dev.tsv

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tsv_all_source_target/test.tsv

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tsv_all_source_target/train.tsv

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