How to Build an AI Voice Translator App Using Flutter and Back4App
In this tutorial, you will learn how to build an AI Voice Translator app using Flutter as the frontend framework and Back4App as the backend service. The app will allow users to translate speech, text, and images across multiple languages. It will feature AI-powered translation, optical character recognition (OCR), and speech recognition functionalities. By the end of this tutorial, you'll have built an app that can handle real-time translations and store history on Back4App for future use.
To complete this tutorial, you will need:
- Basic knowledge of Dart and Flutter. If you're new to Flutter, review the Flutter documentation before proceeding.
- An account with a Translation API provider like Google Cloud Translation or DeepL.
- Familiarity with REST APIs and asynchronous programming in Dart.
In this step, you will set up a Back4App application, define the data models, and configure the backend to store translation history, languages, and user data.
- Click on "Create new App".
- Enter an App Name (e.g., "AI Voice Translator") and select your App Icon.
- Choose your server location if prompted.
- Click "Create".
- Navigate to App Settings > Security & Keys in your app's dashboard.
- Note down the Application ID and Client Key. These will be required for the Flutter app configuration.
We will create the following classes in Back4App:
- User (default)
- Translation
- Language
- Phrase
- DictionaryEntry
1.3.1. Create the Translation Class
- Go to Database > Browser.
- Click "Create a class".
- Choose "Custom" and name it Translation.
- Click "Create class".
Add the following columns to Translation:
- user (Pointer<_User>): Points to the User object.
- sourceLanguage (String): Source language code.
- targetLanguage (String): Target language code.
- sourceText (String): The original text to translate.
- translatedText (String): The translated text.
- translationType (String): Type of translation (voice, text, image).
- timestamp (DateTime).
1.3.2. Create the Language Class
- Repeat the steps to create a new class named Language.
Add the following columns to Language:
- name (String): The name of the language (e.g., "English").
- code (String): ISO code of the language (e.g., "en").
- flagIconUrl (String): URL of the flag image representing the language.
1.3.3. Create the Phrase Class
- Create a class named Phrase.
Add the following columns to Phrase:
- category (String): The category of the phrase (e.g., "Greetings").
- sourceLanguage (String): Source language code.
- targetLanguage (String): Target language code.
- sourceText (String): The original phrase.
- translatedText (String): The translated phrase.
1.3.4. Create the DictionaryEntry Class
- Create a class named DictionaryEntry.
Add the following columns to DictionaryEntry:
- word (String): The word being defined.
- language (String): The language of the word.
- definition (String): The word’s definition.
- examples (Array): Example sentences using the word.
Ensure that only authenticated users can access their own data:
- For each class, go to Security > Class-Level Permissions (CLP).
- Set the CLP to allow read/write access only to authenticated users.
In this step, you'll set up a Flutter project and configure it to connect to Back4App.
Open your terminal and run:
Navigate to the project directory:
Open pubspec.yaml and add the following dependencies:
Run flutter pub get to install the packages.
Create a new file lib/config/back4app_config.dart:
Replace 'YOUR_APPLICATION_ID' and 'YOUR_CLIENT_KEY' with the keys from Back4App.
In lib/main.dart, initialize Parse:
Create lib/app.dart:
The first feature to implement is basic text translation.
Create lib/services/translation_service.dart to manage interactions with a translation API (Google Cloud Translation API or DeepL).
Create lib/models/language.dart to represent supported languages.
Create lib/screens/text_translation_screen.dart to handle text input and translation:
In this step, you'll add voice translation by integrating speech-to-text and text-to-speech functionalities.
Create lib/services/speech_recognition_service.dart using the speech_to_text package:
Create lib/services/tts_service.dart using the flutter_tts package:
Create lib/screens/voice_translation_screen.dart to handle voice translation:
Create lib/services/ocr_service.dart using the google_ml_kit package:
Create lib/screens/image_translation_screen.dart to handle image input and OCR:
In this step, you'll implement saving translation history and managing a phrase book.
Update lib/services/translation_service.dart to save translation history in Back4App:
Create lib/screens/phrase_book_screen.dart to manage common phrases:
By following this tutorial, you have built a feature-rich AI Voice Translator App with Flutter and Back4App. You implemented:
- Basic and advanced text translation.
- Voice-to-voice translation using speech recognition and text-to-speech.
- Image-to-text translation using OCR.
- Translation history management and a phrase book for common expressions.
- Enhance UI/UX: Improve the app’s interface for a smoother user experience.
- Improve Error Handling: Add error handling and fallback mechanisms for API failures.
- Implement Offline Mode: Cache common translations, phrases, and history for offline access.
- Deploy the App: Prepare the app for deployment to iOS and Android platforms.