diff --git a/Language_Translator/README.MD b/Language_Translator/README.MD deleted file mode 100644 index 555d1effe..000000000 --- a/Language_Translator/README.MD +++ /dev/null @@ -1,102 +0,0 @@ -# Spoken Language Translator 🔊🗣🤖 - -🔹I created a Language translator that automatically detects the language of the input text and translates it into the selected language. - -🔹It uses advanced machine learning algorithms to detect the language of the input text and translate it into the desired language. - -🔹This project utilizes the power of machine learning and natural language processing to provide accurate and efficient translations for various languages. - -## Goal 🎯 - -🔹The goal of this project is to develop a robust language translator that can accurately detect the language of the input text and translate it into the desired language. - -🔹This tool aims to facilitate communication across different languages and cultures, making it useful for individuals, businesses, and organizations worldwide. - -## Dataset 📊 - -🔹The Language Translator project does not require a specific dataset for training. Instead, it utilizes the Google Translate API for language detection and translation. - -🔹The API handles the language processing and translation tasks, making it unnecessary to use a separate dataset for this project. - -## Methodology 🔎 - -🔹The Language Translator project follows a structured approach to translate text from one language to another. Key steps include: - -1. **Language Detection**: Automatically detect the language of the input text using machine learning algorithms. -2. **Translation**: Translate the input text into the desired language using pre-trained translation models. -3. **User Interface**: Provide a user-friendly interface for users to enter text and select the desired language for translation. -4. **Integration**: Integrate the language detection and translation functionalities into a seamless application for easy use. - -## Technologies Used 🚀 - -1. **Python**: For programming the language translator application. -2. **Natural Language Toolkit (NLTK)**: For natural language processing tasks such as tokenization, tagging, and parsing. -3. **Google Translate API**: For translating text from one language to another. -4. **Flask**: For building the web application and providing a user interface. -5. **HTML/CSS**: For designing the front-end of the web application. -6. **JavaScript**: For enhancing the user interface and providing interactive features. - -## Features 💡 - -- **Language Detection**: Automatically detect the language of the input text. -- **Translation**: Translate the input text into the selected language. -- **User Interface**: Provide a simple and intuitive interface for users to interact with the translator. -- **Multiple Languages**: Support translation for a wide range of languages to cater to diverse user needs. - -## Setup ⚙️ - -Before running the application, ensure you have the following libraries installed: - -- **Python**: Make sure you have Python installed on your system. You can download it from the official Python website: [https://www.python.org/downloads/](https://www.python.org/downloads/) - -- **NLTK**: Install the Natural Language Toolkit (NLTK) library using pip: - - `pip install nltk` - -- **Google Translate API**: Obtain the Google Translate API key and install the Google Translate library using pip: - - `pip install googletrans==4.0.0-rc1` - -- **Flask**: Install Flask for building the web application: - - `pip install Flask` - -- **Other Dependencies**: You may need to install other dependencies based on your system and requirements. Refer to the `requirements.txt` file for a complete list of dependencies. - -## Results 📢 - -🔹The Language Translator project has been successfully implemented and provides accurate translations for a wide range of languages. - -🔹The Google Translate API's advanced machine learning algorithms ensure that translations are accurate and reliable, making it a valuable tool for communication across different languages and cultures. - -## 📌 Conclusion - -🔹The Language Translator project demonstrates the power of machine learning and natural language processing in facilitating cross-language communication. - -🔹By automatically detecting the language of the input text and providing accurate translations, the tool helps bridge the language barrier and enables users to communicate effectively in different languages. - -🔹The project's use of the Google Translate API showcases the capabilities of modern machine learning algorithms in handling complex language processing tasks. - - -## Usage 🧩✍ - -1. **Clone the Repository**: - - `git clone https://github.com/yourusername/language-translator.git` - -2. **Install Dependencies**: - - `pip install -r requirements.txt` - -3. **Run the Application**: - - `python app.py` - -4. **Access the Translator**: Open your web browser and navigate to `http://localhost:5000` to access the language translator application. - - -## Future Work ⭐ - -- **Improved Language Detection**: Enhance the accuracy of language detection using advanced machine learning techniques. -- **Additional Features**: Add features such as text-to-speech conversion and language identification for multilingual texts. -- **Performance Optimization**: Optimize the translation process for faster and more efficient translations. \ No newline at end of file diff --git a/Language_Translator/translator.py b/Language_Translator/translator.py deleted file mode 100644 index 432ad2e39..000000000 --- a/Language_Translator/translator.py +++ /dev/null @@ -1,94 +0,0 @@ -from tkinter import * -from googletrans import Translator -import win32com.client as wincl -import speech_recognition as sr -class translator: - - def translate(self): - if str(self.fn.get())!="": - self.translatedfinal = self.translator.translate(str(self.fn.get()), dest=self.variable.get()) - else: - self.translatedfinal = self.translator.translate(self.text, dest=self.variable.get()) - - self.name = Label(self.root, text="Translated Text:", bg='black',fg='cyan',font='1') - self.name.place(x=100, y=400) - self.final = Label(self.root, text=self.translatedfinal.text+" ", font=100,bg='black',fg='cyan') - self.final.place(x=400, y=400) - - - def __init__(self): - self.root = Tk() - self.root.geometry('900x700') - self.root.title("Translator") - self.root.config(bg='black') - self.speak = wincl.Dispatch("SAPI.SpVoice") - - self.raw = "" - self.fn = StringVar() - self.ln = StringVar() - self.translator = Translator() - - self.languages = [ - "English", - "Hindi", - "Telugu", - "Tamil", - "Kannada", - "Malayalam", - "Marathi", - "Gujarati", - "Bengali", - "Punjabi", - "Odia", - "Nepali", - "Sindhi", - "Sanskrit", - "Russian", - "French", - "Arabic", - "Bulgarian", - "Danish", - "German", - "Greek", - "Persian", - "Italian", - "Japanese", - "Korean", - "Polish", - "Urdu", - "Chinese", - "Dutch", - "Spanish", - "Portuguese", - "Romanian", - "Swedish", - "Turkish", - "Vietnamese", - "Afrikaans" - ] - - - self.name = Label(self.root, text="Language Translator", bg='black',fg='cyan') - self.name.config(font=("Old Stamper",30)) - self.name.place(x=200, y=130) - - self.input = Label(self.root, text="Enter text here:", bg='black',fg='cyan',font=100) - self.input.place(x=100, y=305) - - self.firste = Entry(self.root, textvariable=self.fn, bg='black', fg='cyan',font='10') - self.firste.place(x=280, y=305) - - - self.trans = Button(self.root, text="Translate", bd=7, bg='black', fg='cyan',command=self.translate) - self.trans.place(x=600, y=500) - - self.variable = StringVar(self.root) - self.variable.set(self.languages[0]) - - w=OptionMenu(self.root,self.variable,*self.languages) - w.config(bg='black',fg='cyan',border=0) - w.place(x=600,y=305) - - self.root.mainloop() - -s = translator()