Sixth International Conference on Spoken Language Processing
(ICSLP 2000)

Beijing, China
October 16-20, 2000

Constrained Maximum Likelihood Linear Regression for Speaker Adaptation

Mohamed Afify, Olivier Siohan

Multimedia Communications Research Lab, Bell Laboratories, Lucent Technologies, Murray Hill, NJ, USA

This paper proposes a new structure for use in MLLR adaptation aiming at constraining the transform for potentially better parameter estimation from sparse adaptation data. Motivations for the use of the new structure, and EM based parameter estimation are presented. Experimental results on Spoke3 of the Wall Street Journal task revealed that the proposed transformations outperform a full matrix for a small amount of adaptation data and performs equally well for large adaptation set. They also outperform diagonal transformations for all amounts of adaptation data.

Full Paper

Bibliographic reference.  Afify, Mohamed / Siohan, Olivier (2000): "Constrained maximum likelihood linear regression for speaker adaptation", In ICSLP-2000, vol.3, 861-864.