Voiced/Unvoiced classification of speech with applications to the U.S. government LPC-10E algorithm

This paper describes the development and application of a new voicing algorithm used in the 2400 bit per second U.S. Government´s Enhanced Linear Predictive Coder (LPC-10E). Correct voicing is crucial to perceived quality and naturalness of LPC systems and therefore to user acceptance of LPC systems. This new voicing algorithm uses a smoothed adaptive linear discriminator to classify the signal as voiced or unvoiced speech. The classifier was determined using Fisher´s method of linear discriminant analysis. The voicing decision smoother is a modified median smoother that uses both the linear discriminant and speech onsets to determine its smoothing. The voicing classifier adapts to various acoustic noise levels and features a powerful new set of signal measurements: biased zero crossing rate, energy measures, reflection coefficients, and prediction gains. The LPC-10E voicing algorithm improves upon other 2400 bps LPC voicing algorithms by providing higher quality synthesized speech. Higher quality is due to halving of the error rate and graceful degradation in the presence of acoustic noise.