Speech reconstruction from mel-frequency cepstral coefficients via ?1-norm minimization

This paper presents a high quality speech reconstruction method from Mel-frequency cepstral coefficients (MFCC). Due to the sparse characteristic of the power spectrum of speech, the ℓ₁-norm minimization method is used to tackle the under-determined nature of the speech reconstruction problem. The phase spectrum is recovered by the well-known LSE-ISTFTM algorithm. Experimental results demonstrate that the quality of the reconstructed speech is dramatically improved than the common ℓ₂-norm minimization method, it sounds very close to the original speech when using the high-resolution MFCC, the PESQ score reaches 4.0.