AudioSplit.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"Q6-yPQUSJ9b_"},"outputs":[],"source":["pip install praatio"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"xLUCk3BbwmH2"},"outputs":[],"source":["pip install pydub"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"fMbGwz8zjzvO"},"outputs":[],"source":["pip install librosa"]},{"cell_type":"code","execution_count":4,"metadata":{"id":"bJwMp0vptlKv","executionInfo":{"status":"ok","timestamp":1680480363245,"user_tz":-480,"elapsed":363,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["from praatio import textgrid\n","from pydub import AudioSegment\n","import os\n","import random\n","import shutil\n","import json\n","import librosa"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11460,"status":"ok","timestamp":1680480378846,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"},"user_tz":-480},"id":"EBK4PBYnkAo4","outputId":"a75bf311-a815-485b-cc58-90e9b4945cf7"},"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"markdown","metadata":{"id":"UzV56ftrayhC"},"source":["Step 1: text train split based on the original set provided"]},{"cell_type":"code","execution_count":6,"metadata":{"id":"S_1Q5PzW_VZo","executionInfo":{"status":"ok","timestamp":1680480384055,"user_tz":-480,"elapsed":334,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["\n","def test_train_split(source_audio,dest_audio_train,dest_audio_test,source_transcript,dest_transcript_train,dest_transcript_test,num):\n"," \n","  src_dir = source_transcript\n","  #dst_dir = dest_transcript\n","  arr_dir = [dest_audio_train,dest_audio_test,dest_transcript_train,dest_transcript_test]\n","  #clearing the test folder for both transcript and audio\n","  for dest_dir in arr_dir:\n","    for filename in os.listdir(dest_dir):\n","        f = os.path.join(dest_dir, filename)\n","          # checking if it is a file\n","        if os.path.isfile(f):\n","            os.remove(f)\n","\n","  # Get a list of all the file names in the source directory\n","  files = os.listdir(src_dir)\n","  print(files)\n","  # Shuffle the list of file names\n","  random.shuffle(files)\n","\n","  # Split the list into two equal parts (pass test file num as num)\n","\n","  split_index = len(files) // num\n","  #print(str(len(files)) + \"len(files)\")\n","  files_a = files[:split_index]\n","  files_b = files[split_index:]\n","\n","  # Copy the files in the first list to the destination directory\n","  for file_name in files_b:\n","      src_path = os.path.join(src_dir, file_name)\n","      dst_path = os.path.join(dest_transcript_train, file_name)\n","      src_path_audio = os.path.join(source_audio, file_name.replace(\".TextGrid\",\".wav\"))\n","      dst_path_audio = os.path.join(dest_audio_train, file_name.replace(\".TextGrid\",\".wav\"))\n","      #print(\"dst_path\" + dst_path)\n","      #print(\"dst_path_audio\" + dst_path_audio)\n","      shutil.copy(src_path, dst_path)\n","      shutil.copy(src_path_audio, dst_path_audio)\n","\n","\n","  # Copy the files in the second list to the test directory\n","  for file_name in files_a:\n","      src_path = os.path.join(src_dir, file_name)\n","      dst_path = os.path.join(dest_transcript_test, file_name)\n","      src_path_audio = os.path.join(source_audio, file_name.replace(\".TextGrid\",\".wav\"))\n","      dst_path_audio = os.path.join(dest_audio_test, file_name.replace(\".TextGrid\",\".wav\"))\n","      #print(\"dst_path\" + dst_path)\n","      #print(\"dst_path_audio\" + dst_path_audio)\n","      shutil.copy(src_path, dst_path)\n","      shutil.copy(src_path_audio, dst_path_audio)\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"V6jk2rblchfy"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":29,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":12554,"status":"ok","timestamp":1680482351086,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"},"user_tz":-480},"id":"DA5hGX2UHhe2","outputId":"88bb3073-8fb8-45b2-d127-9b0e11429d67"},"outputs":[{"output_type":"stream","name":"stdout","text":["['app_3562_5123_phnd_fin.TextGrid', 'app_1977_0041_phnd_cc-moe.TextGrid', 'app_0030_0001_phnd_cc-res.TextGrid', 'app_3410_4819_phnd_fin.TextGrid', 'app_0404_0004_phnd_cc-hol.TextGrid', 'app_3464_4928_phnd_fin.TextGrid', 'app_0493_0001_phnd_cc-res.TextGrid', 'app_3660_5319_phnd_neg.TextGrid', 'app_0322_0001_phnd_cc-hot.TextGrid', 'app_1854_0032_phnd_cc-moe.TextGrid', 'app_3392_4784_phnd_fin.TextGrid', 'app_0297_0001_phnd_cc-hot.TextGrid', 'app_1622_0018_phnd_cc-hdb.TextGrid', 'app_3728_5455_phnd_fin.TextGrid', 'app_3401_4801_phnd_fin.TextGrid', 'app_1953_0014_phnd_cc-moe.TextGrid', 'app_0268_3536_phnd_cc-res.TextGrid', 'app_3631_5262_phnd_fin.TextGrid', 'app_3518_5035_phnd_fin.TextGrid', 'app_1523_0003_phnd_cc-hdb.TextGrid', 'app_0321_0001_phnd_cc-res.TextGrid', 'app_1370_5740_phnd_cc-msf.TextGrid', 'app_0486_0024_phnd_cc-hot.TextGrid', 'app_2055_7010_phnd_cc-msf.TextGrid', 'app_0267_3534_phnd_cc-res.TextGrid', 'app_0554_0022_phnd_cc-hol.TextGrid', 'app_3091_4181_phnd_fin.TextGrid', 'app_3124_4247_phnd_fin.TextGrid', 'app_3738_5476_phnd_neg.TextGrid', 'app_0320_0001_phnd_cc-hot.TextGrid', 'app_3767_5534_phnd_fin.TextGrid', 'app_3590_5179_phnd_fin.TextGrid', 'app_1639_0018_phnd_cc-hdb.TextGrid', 'app_0661_0012_phnd_cc-res.TextGrid', 'app_3456_4911_phnd_fin.TextGrid', 'app_1578_6156_phnd_cc-msf.TextGrid', 'app_3429_4858_phnd_fin.TextGrid', 'app_3748_5495_phnd_fin.TextGrid', 'app_3406_4812_phnd_fin.TextGrid', 'app_3648_5295_phnd_fin.TextGrid', 'app_3210_4420_phnd_fin.TextGrid', 'app_1568_6136_phnd_cc-moe.TextGrid', 'app_3768_5535_phnd_neg.TextGrid', 'app_0434_0004_phnd_cc-hol.TextGrid', 'app_0263_3526_phnd_cc-hot.TextGrid', 'app_3146_4291_phnd_fin.TextGrid', 'app_1984_0014_phnd_cc-hdb.TextGrid', 'app_3761_5522_phnd_fin.TextGrid', 'app_2042_0018_phnd_cc-moe.TextGrid', 'app_3204_4407_phnd_fin.TextGrid', 'app_3733_5466_phnd_fin.TextGrid', 'app_1950_6900_phnd_cc-msf.TextGrid', 'app_3227_4453_phnd_fin.TextGrid', 'app_3149_4298_phnd_fin.TextGrid', 'app_3745_5489_phnd_fin.TextGrid', 'app_3184_4367_phnd_pos.TextGrid', 'app_1706_6412_phnd_cc-moe.TextGrid', 'app_3596_5191_phnd_fin.TextGrid']\n"]}],"source":[" ### invoke test train split\n","\n"," #num indicates basically what fraction to go as the test set. I am choosing 1/4 th hence passing 4 as num\n","num = 4\n","src_transcript_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/original'\n","dst_transcript_train_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/train'\n","dst_transcript_test_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/test'\n","\n","##splitting audio for train and test\n","src_audio_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/original'\n","dst_audio_train_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train'\n","dst_audio_test_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/test'\n","\n","test_train_split(src_audio_dir,dst_audio_train_dir,dst_audio_test_dir,src_transcript_dir,dst_transcript_train_dir,dst_transcript_test_dir,num)"]},{"cell_type":"code","execution_count":30,"metadata":{"id":"6GLOPrPGA3OP","executionInfo":{"status":"ok","timestamp":1680482366978,"user_tz":-480,"elapsed":980,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["##Define the tier name, input/out for audio and textgrid files\n","\n","tier_name = \"channel1_S1\" # Replace this with the actual name of the tier you want to work with\n","\n","## Input and target for Textgrid and targer .csv files\n","\n","manifest_path  = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/\"\n","input_textgrid_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts\"\n","target_script_dir = '/transcripts_processed'\n"," \n"," ## Input and target for audio and target split audio files \n","input_audio_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio\"\n","target_audio_dir = '/audio_processed'\n","\n","src_transcript_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/original'\n","dst_transcript_train_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/train'\n","dst_transcript_test_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/test'\n","#test_train_split(src_transcript_dir,dst_transcript_dir,num);\n","\n","##splitting audio for train and test\n","src_audio_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/original'\n","dst_audio_train_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train'\n","dst_audio_test_dir = '/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/test'\n","\n","\n","textgrid_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train\"\n","audio_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train\"\n","textgrid_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/test\"\n","audio_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/test\""]},{"cell_type":"code","execution_count":10,"metadata":{"id":"Q4fXv_hzMlxV","executionInfo":{"status":"ok","timestamp":1680480826518,"user_tz":-480,"elapsed":8,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["\n","def extract_intervals(textgrid_file, tier_name):\n"," tg = textgrid.openTextgrid(textgrid_file,False)\n","  #print(tg.tierNames)\n","  #print(tg.tiers)\n","  # Get the tier you want to work with\n"," #tier = tg.get_tier_by_name(tier_name)\n"," tier = tg.getTier(tier_name)\n"," print(tier.entries)\n","  # Extract xmin, xmax, and label (text) from the tier's entries\n"," intervals = [(entry.start, entry.end, entry.label) for entry in tier.entries]\n"," return intervals\n"]},{"cell_type":"code","execution_count":18,"metadata":{"id":"Mj8KvPeVw0Yh","executionInfo":{"status":"ok","timestamp":1680481726033,"user_tz":-480,"elapsed":8,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["def split_wav_file(input_file, start_time, end_time, output_file):\n","# Load the input .wav file\n","    audio = AudioSegment.from_wav(input_file)\n","    # Convert start and end time to milliseconds\n","    start_time_ms = start_time * 1000\n","    end_time_ms = end_time * 1000\n","    # Slice the audio\n","    sliced_audio = audio[start_time_ms:end_time_ms]\n","    # Export the sliced audio to a new .wav file\n","    #return sliced_audio\n","    sliced_audio.export(output_file, format=\"wav\")"]},{"cell_type":"code","execution_count":12,"metadata":{"id":"Lyq2-u0hdIxx","executionInfo":{"status":"ok","timestamp":1680480832408,"user_tz":-480,"elapsed":1398,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["# Function to build a manifest\n","def build_manifest(transcripts_path, manifest_path, wav_path):\n","    audio_paths=[]; durations=[]; texts=[]\n","    with open(transcripts_path, 'r') as fin:\n","        with open(manifest_path, 'a') as fout:\n","            for line in fin:\n","                # Lines look like this:\n","                # <s> transcript </s> (fileID)\n","                #transcript = line[: line.find('(')-1].lower()\n","                #print(\"line after processing step 1\" + transcript)\n","                transcript = line.replace('<s>', '').replace('</s>', '')\n","              # print(\"line after processing step 2\" + transcript)\n","                transcript = transcript.strip()\n","                #print(\"line after processing step 3\" + transcript)\n","\n","\n","                file_id = line[line.find('(')+1 : -2]  # e.g. \"cen4-fash-b\"\n","                #audio_path = os.path.join(\n","                #    data_dir, wav_path,\n","                #   file_id[file_id.find('-')+1 : file_id.rfind('-')],\n","                #   file_id + '.wav')\n","                #print(\"line = \" + line)\n","            \n","                #print(\"transcript = \" + transcript)\n","              \n","                duration = librosa.core.get_duration(filename=wav_path)\n","\n","                #audio_paths.append(audio_path)\n","                audio_paths.append(wav_path)\n","                durations.append(duration)\n","                texts.append(transcript)\n","                # Write the metadata to the manifest\n","                metadata = {\n","                    \"audio_filepath\": wav_path,\n","                    \"duration\": duration,\n","                    \"text\": transcript\n","                }\n","                json.dump(metadata, fout)\n","                fout.write('\\n') \n","    return audio_paths, durations, texts"]},{"cell_type":"code","execution_count":13,"metadata":{"id":"FeiSkGxnBC8u","executionInfo":{"status":"ok","timestamp":1680480835590,"user_tz":-480,"elapsed":308,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["def cleanupfolders():\n","    #%cd /content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject\n","    textgrid_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train\"\n","    audio_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train\"\n","    textgrid_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/test\"\n","    audio_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/test\"\n","    adhoc_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed\"\n","    adhoc_folder2 = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed\"\n","    folders = [adhoc_folder,adhoc_folder2,textgrid_folder_train,audio_folder_train,textgrid_folder_test,audio_folder_test]\n","    for folder in folders:\n","      print(folder)\n","      for filename in os.listdir(folder):\n","        i = 0\n","        #print(filename)\n","        f = os.path.join(folder, filename)\n","        # checking if it is a file\n","        if os.path.isfile(f):\n","            #print(f)\n","            #tg = textgrid.openTextgrid(f,False)\n","            os.remove(f)\n","\n","    for filename in os.listdir(textgrid_folder_train):\n","        i = 0\n","        f = os.path.join(textgrid_folder_train, filename)\n","        # checking if it is a file\n","        if os.path.isfile(f):\n","            #print(f)\n","            #tg = textgrid.openTextgrid(f,False)\n","            #print(filename)\n","            #if  '.txt' in filename:\n","            os.remove(f)\n"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":45025,"status":"ok","timestamp":1680479963415,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"},"user_tz":-480},"id":"UgTG9-2oNcQ_","outputId":"f085d909-03b8-4249-f338-da294c4b0b25"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/test\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/test\n"]}],"source":["##claen up existing train and test processed folders if you are going to pre-process the data\n","cleanupfolders()"]},{"cell_type":"code","execution_count":32,"metadata":{"id":"jsacOZ1v8JA2","executionInfo":{"status":"ok","timestamp":1680482431569,"user_tz":-480,"elapsed":412,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["\n","def dataprocessing(input_textgrid_folder,type):\n"," \n","  manifest_file = \"\"\n","  if type == \"train\":\n","    manifest_file = \"manifest_train.json\"\n","  else:\n","     manifest_file = \"manifest_test.json\"\n","  manifest_file = manifest_path + manifest_file\n","\n","  if os.path.isfile(manifest_file):\n","    #if  '.txt' in filename:\n","    os.remove(manifest_file)\n","    print(\"file removed\")\n"," # m_file  = open(manifest_file,\"w\")\n","  arr_dir = []\n","  if type==\"train\":\n","      arr_dir = [textgrid_folder_train,audio_folder_train]\n","  else:\n","      arr_dir = [textgrid_folder_test,audio_folder_test]\n","#deleting exiting files in the folders\n","  for folder in arr_dir:\n","      print(folder)\n","      for filename1 in os.listdir(folder):\n","        i = 0\n","        #print(filename)\n","        f = os.path.join(folder, filename1)\n","        # checking if it is a file\n","        if os.path.isfile(f):\n","            #print(f)\n","            #tg = textgrid.openTextgrid(f,False)\n","            os.remove(f)\n","  print (\"source = \" + input_textgrid_folder)\n","\n","\n","#textgrid_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train\"\n","#audio_folder_train = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train\"\n","#textgrid_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/test\"\n","#audio_folder_test = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/test\"\n","  for filename in os.listdir(input_textgrid_folder):\n","      i = 0\n","      f = os.path.join(input_textgrid_folder, filename)\n","      # checking if it is a file\n","      if os.path.isfile(f):\n","          #print(f)\n","          tg = textgrid.openTextgrid(f,False)\n","          #audiofile = os.path.join(input_audio_folder, f.replace(\".TextGrid\",\".wav\"))\n","          audiofile = f.replace(\".TextGrid\",\".wav\")\n","          audiofile = audiofile.replace(\"/transcripts\",\"/audio\")\n","          #print(\"audio file = \" + audiofile)\n","          #print(\"transcript file = \" + f)\n","          #audiofile = f.replace(subst,\"-\"+str(i)+'.txt')\n","          #print(tg.tierNames)\n","          #print(tg.tiers)\n","            # Get the tier you want to work with\n","          #tier = tg.get_tier_by_name(tier_name)\n","          tier = tg.getTier(tier_name)\n","          #print(tier.entries)\n","            # Extract xmin, xmax, and label (text) from the tier's entries\n","          intervals = [(entry.start, entry.end, entry.label) for entry in tier.entries]\n","          #intervals = extract_intervals(textgrid_file, tier_name)\n","          i = 0\n","          for xmin, xmax, text in intervals:\n","            #print(f\"Start: {xmin}, End: {xmax}, Text: {text}\")\n","            #f = f+ str(i)\n","            i = i+1\n","            ln =len(f)-9\n","            #print('subst' + str(ln))\n","            subst = f[ln:ln+9]\n","\n","            audioln =len(audiofile)-7\n","            #print('subst' + str(ln))\n","            audiosubst = audiofile[audioln:audioln+3]\n","            #print('audiosubst : ' + audiosubst)\n","\n","            fname = f.replace(subst,\"-\"+str(i)+'.txt')\n","            audioName = audiofile.replace(audiosubst,audiosubst+\"-\"+str(i))\n","            #fname = fname.replace(subst,'_'+str(i)+ '.txt')\n","            #print('audioName' + audioName )\n","            #/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/original/app_0030_0001_phnd_cc-res.TextGrid\n","            #target_script_dir = '/transcripts_processed'\n"," \n"," ## Input and target for audio and target split audio files \n","#input_audio_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio\"\n","#target_audio_dir = '/audio_processed'\n","            fname = fname.replace(\"/transcripts\",target_script_dir)\n","            audioName = audioName.replace(\"/audio\",target_audio_dir)\n","            print('fname' + fname )\n","            print('audioName' + audioName )\n","            if  (text != \"\" and  text != \"<S>\"):\n","\n","              file  = open(fname,\"w\")\n","              #with open(fname,\"w\") as file:\n","              #print('fname=' + fname)\n","              file.write(text)\n","              file.close()\n","              split_wav_file(audiofile, xmin, xmax, audioName)\n","              #if os.path.isfile(f):\n","               # print(f)\n","            #tg = textgrid.openTextgrid(f,False)\n","            #print(filename)\n","               \n","              #m_string = str(i)+\",\"+fname+\",\"+audioName+\"\\n\"\n","              #m_file.write(m_string)\n","              build_manifest(fname,manifest_file,audioName)\n"]},{"cell_type":"markdown","metadata":{"id":"2_eNF379k7Yo"},"source":[]},{"cell_type":"code","execution_count":null,"metadata":{"id":"fAAehzy1Kk1d"},"outputs":[],"source":["## split each file under test/trainbased on the duration of the conversation and prepare a manifest\n","dataprocessing(dst_transcript_test_dir,\"test\")\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ygh176bnRcob","colab":{"base_uri":"https://localhost:8080/"},"outputId":"509f4ea8-3037-43b8-fa54-a288ddc75ec0"},"outputs":[{"output_type":"stream","name":"stdout","text":["file removed\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train\n","/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train\n","source = /content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts/train\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3562_5123_phnd_fin-1.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3562_5123_phnd_fin-1.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3562_5123_phnd_fin-2.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3562_5123_phnd_fin-2.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3562_5123_phnd_fin-3.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3562_5123_phnd_fin-3.wav\n"]},{"output_type":"stream","name":"stderr","text":["<ipython-input-12-aedf47931268>:26: FutureWarning: get_duration() keyword argument 'filename' has been renamed to 'path' in version 0.10.0.\n","\tThis alias will be removed in version 1.0.\n","  duration = librosa.core.get_duration(filename=wav_path)\n"]},{"output_type":"stream","name":"stdout","text":["fname/content/drive/MyDrive/Colab Notebooks/AI6127 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NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-121.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-121.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-122.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-122.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-123.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-123.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-124.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-124.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-125.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-125.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-126.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-126.wav\n","fname/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts_processed/train/app_3401_4801_phnd_fin-127.txt\n","audioName/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio_processed/train/app_3401_4801_phnd_fin-127.wav\n"]}],"source":["dataprocessing(dst_transcript_train_dir,\"train\")"]},{"cell_type":"code","execution_count":20,"metadata":{"id":"eeOFvFEmhnBL","executionInfo":{"status":"ok","timestamp":1680481908733,"user_tz":-480,"elapsed":446,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["def count_files(path):\n","    count = 0\n","    for root, dirs, files in os.walk(path):\n","        count += len(files)\n","    return count\n"]},{"cell_type":"code","execution_count":21,"metadata":{"id":"vUqe3X0iiNgB","executionInfo":{"status":"ok","timestamp":1680481910205,"user_tz":-480,"elapsed":3,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}}},"outputs":[],"source":["def getFileStatistics():\n","  %cd  \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject\"\n","  folders = []\n","  for root, dirs, files in os.walk(\"Data\"):\n","          for dir in dirs:\n","              folder_path = os.path.join(root, dir)\n","              if \".ipynb_checkpoints\" not in folder_path:\n","                  count = count_files(folder_path)\n","                  print(\"folder_path = \" + folder_path + \" has  \" + str(count) + \" files \")\n","              #folders.append(folder_path)\n","    \n","\n"]},{"cell_type":"code","execution_count":36,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2242,"status":"ok","timestamp":1680483644740,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"},"user_tz":-480},"id":"qjkbkgM7k7-0","outputId":"bbbe98aa-de03-4bc6-bf78-a70bd1a7de80"},"outputs":[{"output_type":"stream","name":"stdout","text":["/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject\n","folder_path = Data/audio has  116 files \n","folder_path = Data/audio_processed has  6072 files \n","folder_path = Data/transcripts has  116 files \n","folder_path = Data/transcripts_processed has  6072 files \n","folder_path = Data/audio/test has  14 files \n","folder_path = Data/audio/train has  44 files \n","folder_path = Data/audio/original has  58 files \n","folder_path = Data/audio_processed/train has  4862 files \n","folder_path = Data/audio_processed/test has  1210 files \n","folder_path = Data/transcripts/test has  14 files \n","folder_path = Data/transcripts/original has  58 files \n","folder_path = Data/transcripts/train has  44 files \n","folder_path = Data/transcripts_processed/train has  4862 files \n","folder_path = Data/transcripts_processed/test has  1210 files \n"]}],"source":["# get file statistics before file processing\n","\n","getFileStatistics()"]},{"cell_type":"code","source":["folder_path = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data\"\n","output_path = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data\"\n","!zip -r \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data.zip\" \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data\""],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mG7CJMg1SMdC","outputId":"db5b345e-172e-46da-ddab-4c7f1d315736"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Scanning files \n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/ (stored 0%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/ (stored 0%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/.ipynb_checkpoints/ (stored 0%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/test/ (stored 0%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/test/app_1639_0018_phnd_cc-hdb.wav (deflated 38%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/test/app_3748_5495_phnd_fin.wav (deflated 26%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/ (stored 0%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_1984_0014_phnd_cc-hdb.wav (deflated 33%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_1370_5740_phnd_cc-msf.wav (deflated 33%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3091_4181_phnd_fin.wav (deflated 18%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3410_4819_phnd_fin.wav (deflated 30%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_0263_3526_phnd_cc-hot.wav (deflated 15%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3184_4367_phnd_pos.wav (deflated 30%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3149_4298_phnd_fin.wav (deflated 20%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_0297_0001_phnd_cc-hot.wav (deflated 16%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3761_5522_phnd_fin.wav (deflated 26%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3728_5455_phnd_fin.wav (deflated 27%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_1950_6900_phnd_cc-msf.wav (deflated 37%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3767_5534_phnd_fin.wav (deflated 31%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3768_5535_phnd_neg.wav (deflated 21%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3590_5179_phnd_fin.wav (deflated 29%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3596_5191_phnd_fin.wav (deflated 23%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3146_4291_phnd_fin.wav (deflated 20%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3562_5123_phnd_fin.wav (deflated 33%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_3660_5319_phnd_neg.wav (deflated 30%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_1523_0003_phnd_cc-hdb.wav (deflated 22%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train/app_0434_0004_phnd_cc-hol.wav (deflated 25%)\n","updating: content/drive/MyDrive/Colab Notebooks/AI6127 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aiosignal-1.3.1 async-timeout-4.0.2 frozenlist-1.3.3 lightning-utilities-0.8.0 multidict-6.0.4 pytorch_lightning-2.0.1 torchmetrics-0.11.4 yarl-1.8.2\n"]}]},{"cell_type":"code","source":["import pytorch_lightning as pl\n","trainer = pl.Trainer(devices=1, accelerator='gpu', max_epochs=50)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":317},"id":"MNQFsVNTapQL","executionInfo":{"status":"error","timestamp":1680446685744,"user_tz":-480,"elapsed":10,"user":{"displayName":"Shinu Abdulvahab","userId":"13881570554160508866"}},"outputId":"ac92cc82-c9cd-4f0e-afba-c88a22d58caf"},"execution_count":1,"outputs":[{"output_type":"error","ename":"ModuleNotFoundError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)","\u001b[0;32m<ipython-input-1-2b9e86dadd9e>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mpytorch_lightning\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mtrainer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpl\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTrainer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevices\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccelerator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'gpu'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmax_epochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m50\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pytorch_lightning'","","\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"],"errorDetails":{"actions":[{"action":"open_url","actionText":"Open Examples","url":"/notebooks/snippets/importing_libraries.ipynb"}]}}]},{"cell_type":"markdown","metadata":{"id":"cn7szSh5eFKE"},"source":["BeLOW are one time scripts used to copy the files over or to dele"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"EnfamQlNakiR"},"outputs":[],"source":["import shutil\n","import os\n","\n","# Path of the source directory\n","src_dir = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio\"\n","# Path of the destination directory\n","dst_dir = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio/train\"\n","\n","# Get the list of all files in the source directory\n","files = os.listdir(src_dir)\n","\n","# Iterate over all the files and copy them to the destination directory\n","for file_name in files:\n","    \n","      # Construct the full file path\n","      src_file = os.path.join(src_dir, file_name)\n","      dst_file = os.path.join(dst_dir, file_name)\n","\n","      # Copy the file\n","      #print(src_file)\n","      #print(dst_file)\n","      if os.path.isfile(src_file):\n","        print(\"if there is a need to copy enable the below line\")\n","        ##shutil.copy(src_file, dst_file)\n","      #os.remove(src_file)"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"60d8v7h-ONGq"},"outputs":[],"source":["##Renane old files\n","\n","old_audio = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/audio\"\n","old_speech = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts\"\n","counter = 1\n","for filename in os.listdir(old_audio):\n","        filenamenew = filename.replace(\".wav.wav\",\".wav\")\n","        os.rename(os.path.join(old_audio, filename), os.path.join(old_audio, filenamenew))\n","        #os.rename(filename, filenamenew)\n","        #counter += 1\n","\n","for filename in os.listdir(old_speech):\n","        filenamenew = filename.replace(\".wav.TextGrid\",\".TextGrid\")\n","        os.rename(os.path.join(old_speech, filename), os.path.join(old_speech, filenamenew))\n","        #os.rename(filename, filenamenew)\n","        #counter += 1\n","      "]},{"cell_type":"code","execution_count":null,"metadata":{"id":"xTLSYU9xSr9g"},"outputs":[],"source":["import zipfile\n"," # Replace this with the path to your folder\n","#file_name = \"training_pack1.zip\"        # Replace this with the name of your file\n","\n","# Create the file path by joining the folder path and file name\n","\n","\n","\n","zip_file_transcript = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts.zip\"\n","zip_file_transcript_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/transcripts\"\n","zip_folder = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data\"\n","sample = \"/content/drive/MyDrive/Colab Notebooks/AI6127 NLP/GroupProject/Data/sample.zip\"\n","\n","#zip_path = os.path.join(zip_folder, file_name)\n","\n","\n","\n","\n","with zipfile.ZipFile(zip_file_transcript, \"r\") as zip_ref:\n","    zip_ref.extractall(zip_file_transcript_folder)\n","\n","    #file_list = zip_ref.namelist()\n","    #print(file_list)\n","\n"]}],"metadata":{"colab":{"provenance":[],"machine_shape":"hm","mount_file_id":"15p8ZFWaalYIn8xpMJ7FRv7eq37eqnrnT","authorship_tag":"ABX9TyNfCbDPzIu4NuzAbqYDTNTr"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"},"gpuClass":"standard"},"nbformat":4,"nbformat_minor":0}