Enhanced robustness to unvoiced speech and noise in the DYPSA algorithm for identification of glottal closure instants

The DYPSA algorithm detects glottal closure instants (GCI) in speech signals. We present a modification to the DYPSA algorithm in which a voiced/unvoiced/silence discrimination measure is applied in order to reduce spurious GCIs detected by DYPSA for unvoiced speech or silence periods. Speech classification is addressed by formulating a decision rule for the GCI candidates which classifies the candidates as voiced or unvoiced on the basis of feature measurements extracted from the speech signal alone. Dynamic programming is then employed in order to select an optimum set of GCIs from the GCI candidates occurring only during voiced speech. The algorithm has been tested on the APLAWD speech database with 87.23% improvement achieved in reduction of spurious GCIs.