Using a new Discretization of the Fourier Transform to Discriminate Voiced From Unvoiced Speech

In automatic speech recognition, voice synthesis, speaker identification and identifying laringeal diseases, it is critical to classify speech segments as voiced or unvoiced. Several techniques have been proposed for this issue during the last twenty years, unfortunately, they either have especial cases where the result is unreliable or need to use not only the present segment of speech but the next one as well, this fact limits its applications (i.e continuous speech recognition). In this paper we present an alternative to voiced/unvoiced classification using a discretization of the continuous Fourier transform