Using signal processing providing an efficient solution for Speech Recognition
In those Articles, I have discussed the theory behind those systems. And take a use case and design an efficient Automatic Speech Recognition system for it.
- Overview of the ASR system and its theory [https://lnkd.in/dBqy67Bs]
- Use case and its ASR design [https://lnkd.in/dx32qmTz]
This is a repository for an Automatic Speech Recognition System designed using Digital Signal Processing techniques in MATLAB. The system is designed to recognize spoken words and phrases and convert them into text. The system uses various DSP techniques such as filtering, feature extraction, and classification to accurately recognize speech.
- Uses various DSP techniques such as filtering, feature extraction, and classification
- Customizable to recognize specific words and phrases
- Includes a user interface for inputting speech and viewing recognized text
- MATLAB
- Clone the repository
- Open MATLAB and navigate to the cloned repository
- Run the SpeechRecognation.m file
- Open the system in MATLAB
- Use a microphone to input speech
- View the recognized text in the user interface
The system can be customized to recognize specific words and phrases by modifying the code. Users can modify the feature extraction and classification algorithms to improve recognition accuracy.
Contributions to the project are welcome. Users can submit bug reports or feature requests through the project's GitHub repository.
The project is licensed under the MIT License, allowing for free use and modification by anyone.