Time-scale modification of speech signals based on wavelet transform

Time and frequency scale modification of speech signals

This paper presents new and improved methods for independently modifying the time and pitch scale of acoustic signals, with an emphasis on speech signals. The algorithms developed here use parametric (sinusoidal) modelling techniques introduced by other authors, but new ideas are presented here that achieve improved output quality with decreased computational load. In particular, speech quality...

Speech Scrambling Based on Wavelet Transform

The increased interest in analog speech scrambling techniques are due to the increased visibility and publicity given to the vulnerability of communication systems to eavesdropping of unauthorized remote access (Gersho & Steele, 1984). In wireless communications, including High Frequency (H.F) and satellite communications, it is almost impossible to prevent unauthorized people from eavesdroppin...

3 Speech Scrambling Based on Wavelet Transform

Wavelet speech enhancement based on time-scale adaptation

We propose a new speech enhancement method based on time and scale adaptation of wavelet thresholds. The time dependency is introduced by approximating the Teager Energy of the wavelet coefficients, while the scale dependency is introduced by extending the principle of level dependent threshold to Wavelet Packet Thresholding. This technique does not require an explicit estimation of the noise l...

A New Method for Speech Enhancement Based on Incoherent Model Learning in Wavelet Transform Domain

Quality of speech signal significantly reduces in the presence of environmental noise signals and leads to the imperfect performance of hearing aid devices, automatic speech recognition systems, and mobile phones. In this paper, the single channel speech enhancement of the corrupted signals by the additive noise signals is considered. A dictionary-based algorithm is proposed to train the speech...