• Rahul Dang
• Veena Loyal
• Dr. Dinesh Kumar Gupta

it proposes a method for speech enhancement using mask estimation iteratively. In this work, it provides speech enhancement under different noisy conditions. The speech power spectrum varies greatly for different types of speech sound. The energy of voiced speech sounds is concentrated in the harmonics of the fundamental frequency while that of unvoiced sounds is, in contrast, distributed across a broad range of frequencies. To identify the presence of speech energy in a noisy speech signal we have therefore developed two detection algorithms. The first is a robust algorithm that identifies voiced speech segments and estimates their fundamental frequency. The second detects the presence of sibilants and estimates their energy distribution. The use of speech enhancement algorithm removes or reduces the presence of noise. All simulations are implemented in MATLAB.

Speech Enhancement, Speech Processing, Noise Filtering, Sparse Representation etc.

"Quality Measures Evaluation by Hybrid Sparse & Neural in Speech Enhancement", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.15-20, September-2018, Available :http://www.jetir.org/papers/JETIR1809503.pdf

"Quality Measures Evaluation by Hybrid Sparse & Neural in Speech Enhancement", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp15-20, September-2018, Available at : http://www.jetir.org/papers/JETIR1809503.pdf