Abstract: A CELP speech decoder includes a first portion comprising an adaptive codebook and a second portion comprising a fixed codebook. The CS-ACELP decoder generates a speech excitation signal selectively based on output signals from said first and second portions when said decoder fails to receive reliably at least a portion of a current frame of compressed speech information. The decoder does this by classifying the speech signal to be generated as periodic (voiced) or non-periodic (unvoiced) and then generating an excitation signal based on this classification. If the speech signal is classified as periodic, the excitation signal is generated based on the output signal from the first portion and not on the output signal from the second portion. If the speech signal is classified as non-periodic, the excitation signal is generated based on the output signal from said second portion and not on the output signal from said first portion.

Abstract: A noise reducing method for speech signals is provided in which the probability of speech occurring is calculated by spectral subtraction of subtracting the estimated noise spectrum from the spectrum of the input signal, and the maximum likelihood filter is adaptively controlled based upon the calculated speech occurrence probability. Adjustment to an optimum suppression factor may be achieved depending on the SNR of the input speech signal, so that is it unnecessary for the user to effect adjustment prior to practical application. In addition, a method for detecting the noise domain is provided in which the value th employed for finding the threshold value Th.sub.1 for noise domain discrimination is calculated using the RMS value of the current frame or the value th of the previous frame multiplied by the coefficient .alpha., whichever is smaller, and the coefficient .alpha. is changed over depending on the RMS value of the current frame.

Abstract: A method and a device for discriminating a voiced sound from an unvoiced sound or background noise in speech signals are disclosed. Each block or frame of input speech signals is divided into plural sub-blocks and the standard deviation, effective value or the peak value is detected in a detection unit for detecting statistical characteristics from one sub-block to another. A bias detection unit detects a bias on the time scale of the standard deviation, effective value or the peak value to decide whether the speech signals are voiced or unvoiced from one block to another.