Signal estimation from modified short-time Fourier transform
Abstract
An algorithm to estimate a signal from its modified short-time Fourier transform (STFT) is presented. This algorithm is computationally simple and is obtained by minimizing the mean squared error between the STFT of the estimated signal and the modified STFT. Using this algorithm, an iterative algorithm to estimate a signal from its modified STFT magnitude is also developed. The iterative algorithm is shown to decrease, in each iteration, the mean squared error between the STFT magnitude of the estimated signal and the modified STFT magnitude. The major computation involved in the iterative algorithm is the discrete Fourier transform computation, and the algorithm appears to be real-time implementable with current hardware technology. The algorithm developed has been applied to the time-scale modification of speech. The resulting system generates very high-quality speech, and appears to be better in performance than any existing method.
- Publication:
-
IEEE Transactions on Acoustics Speech and Signal Processing
- Pub Date:
- April 1984
- Bibcode:
- 1984ITASS..32..236G
- Keywords:
-
- Data Compression;
- Fourier Transformation;
- Parameter Identification;
- Run Time (Computers);
- Signal Processing;
- Time Series Analysis;
- Algorithms;
- Iterative Solution;
- Optimization;
- Root-Mean-Square Errors;
- Speech Recognition;
- Voice Data Processing;
- Electronics and Electrical Engineering