The Speech-to-Text and Text-to-Speech Translator provides seamless conversion between spoken and written words, along with language translation capabilities. It empowers users to transcribe spoken words into text and transform written text into natural-sounding speech. With the added feature of language translation, it facilitates effective communication across different languages.
- Text-to-Speech Conversion: Transform written text into natural-sounding speech.
- Speech-to-Text Conversion: Easily convert spoken words into written text.
- Language Translation: Seamlessly translate text into different languages.
- Speech-to-Text: Speak into the application to have your words transcribed into written text.
- Text-to-Speech: Enter text into the application and listen to it being converted into speech.
- Language Translation: Provide text and select the target language to translate it.
- Python
- Google Translate API
- gTTS (Google Text-to-Speech) Library
- Flask Framework
- A Noise Background Filteration can be applied to make it easier for the program to capture the user's sound without taking much time
- A more lightweight speech recognition engine can be used to make the program faster: The speech_recognition library utilizes various speech recognition engines, such as Google Web Speech API, Sphinx, and Wit.ai. These engines differ in terms of speed and accuracy. We can experiment with different engines to find one that provides a good balance between speed and accuracy for your application.
- Optimize noise reduction and audio preprocessing: Noise reduction and audio preprocessing techniques can enhance speech recognition accuracy.
Contributions are welcome! If you have any suggestions, bug fixes, or feature enhancements, feel free to submit a pull request.