Classification and separation techniques based on fundamental frequency for speech enhancement

  1. P. Cabañas Molero
Supervised by:
  1. Nicolás Ruiz Reyes Director
  2. P. Vera-Candeas Director

Defence university: Universidad de Jaén

Fecha de defensa: 11 January 2016

  1. Antonio Miguel Peinado Herreros Chair
  2. Damián Martínez Muñoz Secretary
  3. Juan Andrés Morales Cordovilla Committee member

Type: Thesis

Teseo: 421216 DIALNET lock_openRUJA editor


This thesis is focused on the development of new classification and speech enhancement algorithms based, explicitly or implicitly, on the fundamental frequency (F0). The F0 of speech has a number of properties that enable speech discrimination from the remaining signals in the acoustic scene, either by defining F0-based signal features (for classification) or F0-based signal models (for separation). Three main contributions are included in this work: 1) an acoustic environment classification algorithm for hearing aids based on F0 to classify the input signal into speech and nonspeech classes; 2) a frame-by-frame basis voiced speech detection algorithm based on the aperiodicity measure, able to work under non-stationary noise and applicable to speech enhancement; 3) a speech denoising algorithm based on a regularized NMF decomposition, in which the background noise is described in a generic way with mathematical constraints.