We present the DYPSA algorithm for automatic and reliable estimation of glottal closure instants (GCIs) in voiced speech. Reliable GCI estimation is essential for closed-phase speech analysis, from which can be derived features of the vocal tract and, separately, the voice source. It has been shown that such features can be used with significant advantages in applications such as speaker recognition. DYPSA is automatic and operates using the speech signal alone without the need for an EGG or Laryngograph signal. It incorporates a new technique for estimating GCI candidates and employs dynamic programming to select the most likely candidates according to a defined cost function. We review and evaluate three existing methods and compare our new algorithm to them. Results for DYPSA show GCI detection accuracy to within ±0.25ms on 87% of the test database and fewer than 1% false alarms and misses.
It is well known that the performance in terms of misalignment of adaptive algorithms, in general, is dependent on the conditioning of the input signal covariance matrix. For two-channel (stereophonic) adaptive algorithms, this performance is further degraded by the high interchannel coherence between the two input signals. In this paper, we establish the relationship between interchannel coherence of the two input signals and condition of the corresponding covariance matrix for stereo acoustic echo cancellation application. We further show how this relationship affects the misalignment performance of a two-channel frequency-domain adaptive algorithm. We provide simulation results for both WGN and speech input to verify our mathematical analysis.
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