Enhancing Speech Intelligibility with MATLAB & Machine Learning
Budget: ₹12,500 – ₹37,500 INR
The primary goal of this project is to enhance the quality of recorded speech that is affected by multiple types of noise, including background, wind, electrical, and Additive White Gaussian Noise (AWGN). This will be achieved through a combination of noise reduction techniques, improving clarity, and increasing intelligibility to ensure clear speaker identification.
To successfully undertake this project, the following skills and experiences are essential:
- Proficiency in MATLAB & MATLAB APP DESIGNER
- A deep understanding of Digital Signal Processing (DSP)
- Extensive experience in Machine Learning
- Experience in working with specific technologies such as Kalman Filtering, Empirical Mode Decomposition (EMD), and Speech Enhancement Generative Adversarial Networks (SEGAN)
The project will incorporate these technologies and algorithms to create an effective solution. This initiative is an excellent opportunity for those well-versed in DSP, MATLAB, and Machine Learning who are seeking to apply their expertise to promote clearer communication. The successful completion of this project will lead to a significant contribution to speech enhancement technology.
To successfully undertake this project, the following skills and experiences are essential:
- Proficiency in MATLAB & MATLAB APP DESIGNER
- A deep understanding of Digital Signal Processing (DSP)
- Extensive experience in Machine Learning
- Experience in working with specific technologies such as Kalman Filtering, Empirical Mode Decomposition (EMD), and Speech Enhancement Generative Adversarial Networks (SEGAN)
The project will incorporate these technologies and algorithms to create an effective solution. This initiative is an excellent opportunity for those well-versed in DSP, MATLAB, and Machine Learning who are seeking to apply their expertise to promote clearer communication. The successful completion of this project will lead to a significant contribution to speech enhancement technology.