12th Annual Conference of the International Speech Communication Association

Florence, Italy
August 27-31. 2011

Front-End Compensation Methods for LVCSR Under Lombard Effect

Hynek Bořil (1), František Grézl (2), John H. L. Hansen (1)

(1) University of Texas at Dallas, USA
(2) Brno University of Technology, Czech Republic

This study analyzes the impact of noisy background variations and Lombard effect (LE) on large vocabulary continuous speech recognition (LVCSR). Robustness of several front-end feature extraction strategies combined with state-of-the-art feature distribution normalizations is tested on neutral and Lombard speech from the UT-Scope database presented in two types of background noise at various levels of SNR. An extension of a bottleneck (BN) front-end utilizing normalization of both critical band energies (CRBE) and BN outputs is proposed and shown to provide a competitive performance compared to the best MFCC-based system. A novel MFCC-based BN front-end is introduced and shown to outperform all other systems in all conditions considered (average 4.1% absolute WER reduction over the second best system). Additionally, two phenomena are observed: (i) combination of cepstral mean subtraction and recently established RASTALP filtering significantly reduces transient effects of RASTA band-pass filtering and increases ASR robustness to noise and LE; (ii) histogram equalization may benefit from utilizing reference distributions derived from pre-normalized rather than raw training features, and also from adopting distributions from different front-ends.

Full Paper

Bibliographic reference.  Bořil, Hynek / Grézl, František / Hansen, John H. L. (2011): "Front-end compensation methods for LVCSR under lombard effect", In INTERSPEECH-2011, 1257-1260.