Speech To Text Telegram Bot Dart
Introduction
The Speech To Text Telegram Bot Dart project provides a seamless way to convert spoken words into text within Telegram. This project harnesses the power of the whisper-dart library, a comprehensive tool designed for handling conversions from spoken language to written text. This library is an essential component of the system that ensures accurate and efficient transcription without the need for an external API key.
Installation and Setup
Step 1: Clone the Repository
To get started, users first need to clone the project repository from GitHub. This can be done by running the following command in the terminal:
git clone https://github.com/azkadev/speech_to_text_telegram_bot_dart
cd speech_to_text_telegram_bot_dart
Step 2: Install Necessary Packages
Once the repository is cloned, the next step involves installing the required Dart packages. Users can accomplish this using the Dart package manager with the following command:
dart pub get
Step 3: Download and Compile the Whisper Model
The project leverages the whisper-dart model for speech recognition. This requires downloading and compiling the necessary components. Users should execute these commands in their terminal:
whisper_dart
place_whisper_model_and_shared_library_here
whisper.bin
whisper.so
Running the Bot
After setting up the environment, users can launch the bot using the command below. This requires specifying the Telegram bot token, API ID, and API hash:
dart run bin/speech_to_text_telegram_bot_dart.dart --token_bot="token" --api_id="telegram_api_id" --api_hash="telegram_api_hash"
Features
This project transforms Telegram by adding voice-to-text capabilities. Users can speak directly into their chat application, which the bot will then transcribe into text, allowing for a more dynamic and convenient messaging experience. This feature is particularly useful for users who prefer speaking over typing or who are in situations that demand hands-free messaging.
Conclusion
The Speech To Text Telegram Bot Dart project stands out with its use of the whisper-dart library to accomplish accurate voice-to-text conversion without external dependencies. This makes the project an efficient solution for improving communication efficiency within Telegram, aligning with current trends favoring smart, voice-activated devices and applications. Whether for everyday conversation or specific accessibility needs, this project represents a significant advancement in how users interact with technology in their day-to-day communication activities.