NLP-Based-Language-Translator-Using-Google-API-in-python

-Multimodal Translation: Enables translation from speech to target language via speech and text inputs, facilitating seamless communication. -Revolutionary OCR Text-to-Speech: the translation of text from images into speech, offering an unparalleled and powerful solution for image-based content translation.

OUTPUT VIDEO

25.09.2023_02.56.28_REC.mp4

Table of Contents

• About
• Key Features
• Text Processing Algorithms
• Speech Processing Techniques
• Text-Image Processing Techniques
• System Specifications
• Supported Languages
• Installation
• Usage
• Contributing

Key Features

• Multimodal Translation: Enables translation from speech to target language via speech and text inputs.

• Revolutionary OCR Text-to-Speech: Translates text from images into speech for image-based content translation.

• Automatic Language Recognition: Automatically identifies the language of the text or chat.

• Automatic Spell Checker: Detects and highlights misspelled words before translation.

• Specialized Dictionaries: Allows the use of dictionaries tailored to specific topics for more accurate translation.

• Do Not Translate Capability: Marks and excludes specific text from translation, ensuring accuracy for proper names and places.

Text Processing Algorithms

The Multilingual Language Translator with OCR incorporates various text processing algorithms to enhance the translation experience:

• Tokenization: Tokenization splits a text into smaller units, such as words or sentences. This process helps in analyzing and translating text effectively.

• Stemming: Stemming reduces words to their base form, for example, converting "running" to "run." This helps in handling variations of words during translation.

• Lemmatization: Lemmatization converts words to their base form while considering context and part-of-speech (POS). It ensures more accurate translations by preserving the meaning of words.

  

Speech Processing Techniques

The application also includes speech processing techniques to handle spoken language:

• Speech Recognition: Speech recognition is used to convert spoken language into text, making it possible to translate spoken conversations.

• Part-of-Speech (POS) Tagging: POS tagging identifies the grammatical components of speech in a sentence, aiding in the understanding and translation of context.

• Named Entity Recognition (NER): NER identifies and extracts relevant information such as names, places, and dates from speech, making translations more context-aware.

Text-Image Processing Techniques

In addition to text and speech processing, the application utilizes text-image processing techniques:

• Optical Character Recognition (OCR): OCR technology is used to convert printed or handwritten text from images into machine-readable text. This feature enables the translation of text from various sources, including images.

• Object Recognition: Object recognition identifies and labels objects in an image, providing additional context for translation when images contain objects or scenes.

• Text Detection and Extraction: Text detection and extraction techniques are employed to detect and extract text from images. This ensures that text content within images can be accurately translated.

System Specifications

Hardware Requirements

• Processor: Ryzen 5 or higher
• Hard Disk: 250 GB or higher
• RAM: 4 GB (Minimum)

Software Requirements

• Operating System: Windows 7 or higher
• Programming Language: Python

Libraries

To install the required Python libraries, use the following commands:

pip install googletrans pip install pyaudio pip install SpeechRecognition pip install gtts

Ensure that you have these libraries and their specified versions in your requirements.txt file. You can install them using pip install -r requirements.txt.

Usage

To use the Multilingual Language Translator with OCR, follow these steps:

1. Run the application.
2. Choose the desired translation settings.
3. Upload an image with text or input text using the GUI.
4. Perform translations, and utilize additional features as needed.
5. Enjoy seamless multilingual communication!

This application is designed to enhance language translation and communication, making it easier for users to interact across language barriers.

Supported Languages

The Multilingual Language Translator with OCR supports translation to and from the following languages:

• Afrikaans (af)
• Albanian (sq)
• Amharic (am)
• Arabic (ar)
• Armenian (hy)
• Azerbaijani (az)
• Basque (eu)
• Belarusian (be)
• Bengali (bn)
• Bosnian (bs)
• Bulgarian (bg)
• Catalan (ca)
• Cebuano (ceb)
• Chichewa (ny)
• Chinese (Simplified) (zh-cn)
• Chinese (Traditional) (zh-tw)
• Corsican (co)
• Croatian (hr)
• Czech (cs)
• Danish (da)
• Dutch (nl)
• English (en)
• Esperanto (eo)
• Estonian (et)
• Filipino (tl)
• Finnish (fi)
• French (fr)
• Frisian (fy)
• Galician (gl)
• Georgian (ka)
• German (de)
• Greek (el)
• Gujarati (gu)
• Haitian Creole (ht)
• Hausa (ha)
• Hawaiian (haw)
• Hebrew (iw, he)
• Hindi (hi)
• Hmong (hmn)
• Hungarian (hu)
• Icelandic (is)
• Igbo (ig)
• Indonesian (id)
• Irish (ga)
• Italian (it)
• Japanese (ja)
• Javanese (jw)
• Kannada (kn)
• Kazakh (kk)
• Khmer (km)
• Korean (ko)
• Kurdish (Kurmanji) (ku)
• Kyrgyz (ky)
• Lao (lo)
• Latin (la)
• Latvian (lv)
• Lithuanian (lt)
• Luxembourgish (lb)
• Macedonian (mk)
• Malagasy (mg)
• Malay (ms)
• Malayalam (ml)
• Maltese (mt)
• Maori (mi)
• Marathi (mr)
• Mongolian (mn)
• Myanmar (Burmese) (my)
• Nepali (ne)
• Norwegian (no)
• Odia (or)
• Pashto (ps)
• Persian (fa)
• Polish (pl)
• Portuguese (pt)
• Punjabi (pa)
• Romanian (ro)
• Russian (ru)
• Samoan (sm)
• Scots Gaelic (gd)
• Serbian (sr)
• Sesotho (st)
• Shona (sn)
• Sindhi (sd)
• Sinhala (si)
• Slovak (sk)
• Slovenian (sl)
• Somali (so)
• Spanish (es)
• Sundanese (su)
• Swahili (sw)
• Swedish (sv)
• Tajik (tg)
• Tamil (ta)
• Telugu (te)
• Thai (th)
• Turkish (tr)
• Ukrainian (uk)
• Urdu (ur)
• Uyghur (ug)
• Uzbek (uz)
• Vietnamese (vi)
• Welsh (cy)
• Xhosa (xh)
• Yiddish (yi)
• Yoruba (yo)
• Zulu (zu)

With support for this extensive list of languages, the application ensures effective communication across various linguistic boundaries.

Contributing

If you have any questions, suggestions, or contributions, please feel free to reach out to the project maintainer:

Yashas S

Email: yashasmanu123@gmail.com

Installation

1. Clone this repository:

   git clone https://github.com/thebeard000/NLP-Based-Language-Translator-Using-Google-API-in-python.git
   cd NLP-Based-Language-Translator-Using-Google-API-in-python