Neural_Machine_Translation_English_Bengali.ipynb

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      "name": "Neural-Machine-Translation-English-Bengali.ipynb",
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    {
      "cell_type": "markdown",
      "source": [
        "# Neural Machine Translation (English to Bengali)"
      ],
      "metadata": {
        "id": "hIwsNFGkbyRW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Introduction"
      ],
      "metadata": {
        "id": "_8rlx-x1qOs7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Language is the heart of communication. There are $\\sim7,100$ languages all over the world and hence communication between people belonging to two different cultures and having different languages has always been a challenge. Access to good quality translation as well as requirement has never been so high, which we observe currently. Large number of communications taking place online among people who speak different languages is eased by language technologies like automated machine translation, speech recognition and conversion to native languages, etc.\n",
        "\n",
        "So, as a part of The 11th Advanced Summer School on NLP (IASNLP-2022) is scheduled to be held at IIIT Hyderabad, India, whose theme revolved around Speech to Speech Machine Translation (SSMT) in Indian Languages, I have worked in developing a Neural Machine Translation Model for English to North-Eastern Language (in my case Bengali). "
      ],
      "metadata": {
        "id": "PJwewgY4b41i"
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    {
      "cell_type": "markdown",
      "source": [
        "## Problem to Solve"
      ],
      "metadata": {
        "id": "YsMI7-0cqMOB"
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    {
      "cell_type": "markdown",
      "source": [
        "There is a lack of literature and good models for English to North-Eastern language machine translation. Hence, it is necessary to explore the possibility of machine translation for these languages from English. Exploration of neural architechtures is what is needed and it is important to look at the performance of these base-line models in terms of machine translation so that further research and work can be put in to train better models or improve on these models."
      ],
      "metadata": {
        "id": "Theg38A6fe-7"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data"
      ],
      "metadata": {
        "id": "pvivTTVBqBb1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Train Data\n",
        "The data I will be using for training is the parallel corpus provided by Samanantar dataset. It is a huge corpus of source-wise split parallel corpus of one Indian language to other or English and vice-verse. For our case we were only concerned with English to Bengali part of this dataset.\n",
        "\n",
        "I took all the $47$ sources for English and Bengali parallel corpus and combined it into a large parallel corpus with $92,51,703$ parallel sentences. I then shuffled the sentences to obtain a homogeneous mixture of parallel sentences from all sources."
      ],
      "metadata": {
        "id": "ZE5kpm7gg0F7"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "| src | tgt |\n",
        "| --- | --- |\n",
        "Okay, I'll be right there.| \tওকে, এখনই আসছি\n",
        "Give one's lessons.| \tপড়া দেওয়া\n",
        "Much to the Witnesses' surprise, even the pros...|\tসাক্ষীরা অত্যন্ত বিস্মিত হন, এমনকি সরকারি উকিল...\n",
        "I am at your service.| \tআমি তোমাকে সাহায্য করার জন্যই\n",
        "Via Facebook Messenger, Global Voices talked w...| \tগ্লোবাল ভয়েসস বাংলা'র পক্ষ থেকে আমরা যোগাযোগ ক...\n",
        "... \t| \t...\n",
        "A panel of auditors for auditing listed compan... |\tনিরীক্ষা কার্যক্রমে শৃঙ্খলা আনয়নে তালিকাভুক্ত...\n",
        "On this consideration, and on certain conditio...| \tসে কারণে কতিপয় শর্ত সাপেক্ষে এসব যন্ত্রাংশের ...\n",
        "Under these rules, fixed price method for IPOs... |\tএতে অভিহিত মূল্যে আইপিও’র জন্য ফিক্সড প্রাইস প...\n",
        "Steps are being taken to introduce rural ratio... |\tটিআর ও ভিজিএফ এর পরিবর্তে পল্লী রেশনিং কর্মসূচ...\n",
        "I propose to rationalize rates and to introduc... |\tউৎস কর: উৎস করে কয়েকটি ক্ষেত্রে করহার যৌক্তিক...\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "v4pX_l1rhWQO"
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      "cell_type": "markdown",
      "source": [
        "Now, due to computational resource and time constraint training on such a large dataset is impossible. Hence, I opt to use $\\sim 1.7\\%$ of this massive training data.\\\n",
        "I also generated a bigger dataset, which is $\\sim8\\%$ of the entire training data, which is used in training only a few models."
      ],
      "metadata": {
        "id": "XBWy0jfwlNEC"
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      "cell_type": "markdown",
      "source": [
        "### Test Data\n",
        "Now, the test data on which I evaluate the model performance is a set of $\\sim250$ parallel sentences taken from Indic WAT 2021.\n",
        "\n"
      ],
      "metadata": {
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    },
    {
      "cell_type": "markdown",
      "source": [
        "| src | tgt |\n",
        "| --- | --- |\n",
        "Through her work, she spread the message of th...| \tনিজের কর্মেরউদাহরণ স্থাপন করে তিনি মানুষকে সেব...\n",
        "Interacting with beneficiaries and store owner...| \tসারা দেশের ৫ হাজারেরও বেশি স্থান থেকে দোকান মা...\n",
        "These include:| \tএই প্রকল্পগুলির মধ্যে রয়েছে-\n",
        "It is no surprise that today Japan is India’s ...| \tজাপান যে বর্তমানে ভারতের চতুর্থ বৃহত্তম প্রত্য...\n",
        "Record growth in last two and a half years| \tগত আড়াই বছরেরেকর্ড পরিমাণ অগ্রগতি"
      ],
      "metadata": {
        "id": "rglGAWoIqFdW"
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      "cell_type": "markdown",
      "source": [
        "## Data Preparation"
      ],
      "metadata": {
        "id": "ybCpZUTkqSM_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Machine Learning Models (In our case Deep Learning Models), don't understand raw text data and hence this text data in the form of sentences need to be converted to numerical representation (vectors). So, here I will explain how I prepared the data to be fed to the Neural Network Model."
      ],
      "metadata": {
        "id": "z5QRQoYaqZ_A"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "### Tokenization and Normalization"
      ],
      "metadata": {
        "id": "zQRgXrfErMne"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are several types of tokenization and normalization methods based on word level, character level and subword level. Each of them has it's benefits and disadvantages ex. word level tokenization requires huge vocabualary, whereas character level requires fixed vocabulary but the input to the neural network i.e. each sentence becomes very large after tokenization and the model also finds it hard to learn relationship between characters.\n",
        "\n",
        "Hence, I go by subword level tokenization, I use Byte-Pair Encoding to tokenize both the train and test data.\\\n",
        "The Byte-Pair Encoder is trained on the training data(for the bigger training data that is used to generate the byte-pair encoder) for both the source(English) and target(Bengali) languages. I used a vocabulary size of $32,000$ for both English and Bengali language.\\\n",
        "For normalizaion I convert the sentences of lower case and used standard unicode normalization.\\\n",
        "For tokenization the tokenized form of the sentence is a list of integers where the integers stand for the corresponding subword at that index in the vocabualary. I add the `bos`(beginning of sentence) token and the `eos`(end of sentence) token at the start and end of each encoded sentence in both the language. I also have the `unk`(unknown) token for the unknown subwords encountered and and `pad`(padding) token."
      ],
      "metadata": {
        "id": "OzrGQBiJrQAA"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For the following two examples the the BPE was trained on the smaller training data and not the bigger one."
      ],
      "metadata": {
        "id": "ZC4LQ4UT1h7H"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "ENGLISH SENTENCE:  Actually, it didnt.\\\n",
        "ENGLISH BPE SUBWORDS:  \\[ \"▁actually\", \",\", \"▁it\", \"▁didnt\", \".\" ]\\\n",
        "ENGLISH BPE ENCODED: \\[ 2597, 31975, 78, 1138, 31972 ]"
      ],
      "metadata": {
        "id": "vr1qlZ91zN7G"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "BENGALI SENTENCE: সত্যি, ব্যাপারটা ও ভাবে নি।\\\n",
        "BENGALI BPE SUBWORDS:\\[ \"▁সত্যি\", \",\", \"▁ব্যাপারটা\", \"▁ও\", \"▁ভাবে\", \"▁নি\", \"।\" ]\\\n",
        "BENGALI BPE ENCODED:\\[ 1569, 31912, 3981, 56, 1225, 57, 31899 ]"
      ],
      "metadata": {
        "id": "jXw1f4PQ1F9l"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "### Padding"
      ],
      "metadata": {
        "id": "vbCu2R6G1xOa"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Neural Network models expect inputs of fixed length. Hence, I set some maximum length of the encoded input which I will feed our model. I take the maximum tokens allowed per sentence as 60. (`MAX_TOKENS = 60`). So, if any tokenized input is less than 60 in length then, it is padded with `pad` token. So, this makes the input data of the same shape and a 2D tensor of `BATCH_SIZE x MAX_TOKENS`. "
      ],
      "metadata": {
        "id": "7Z4mMelc10Kl"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "Batch-1:\\\n",
        "encoded source shape: (256, 60)\\\n",
        "encoded target shape: (256, 60)\\\n",
        "encoded source example: \\[ 3, 2597, 31975, 78, 1138, 31972, 1, 0, 0, ..., 0]\\\n",
        "encoded target example: \\[ 3, 1569, 31912, 3981, 56, 1225, 57, 31899, 1, 0, ...., 0]\\\n",
        "decoded source example: actually, it didnt.\\\n",
        "decoded target example: সত্যি, ব্যাপারটা ও ভাবে নি।\n"
      ],
      "metadata": {
        "id": "rpW90wxJ6yZT"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "The same is done for the the test data, or a sentence, where we encode and pad it to input in the model."
      ],
      "metadata": {
        "id": "LmxJK7Aw8Xy4"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Models"
      ],
      "metadata": {
        "id": "ohbfLahd8tjR"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "I focussed only on Transformer based architechtures. I changed the Hyperparameters of the Transformer and trained several of these models to compare their performance."
      ],
      "metadata": {
        "id": "dSRLkBrD80WL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Model-1"
      ],
      "metadata": {
        "id": "JmguL51s9PxT"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "4 Heads | 8 Heads\n",
        "--|--\n",
        "`Number of Layers = 2`|`Number of Layers = 2`|\n",
        "`Number of Heads = 8`|`Number of Heads = 4`|\n",
        "`Embedding Dimension = 256`|`Embedding Dimension = 256`|\n",
        "`Key Dimension = 32`|`Key Dimension = 32`|\n",
        "`Value Dimension = 32`| `Value Dimension = 32`| \n",
        "\n",
        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)"
      ],
      "metadata": {
        "id": "2Ap86HKk9XKV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Training Accuracy|Training Loss"
      ],
      "metadata": {
        "id": "7ZcZhqg6Mkfj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "x6E1mRguqWY7"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}