Ninth International Conference on Spoken Language Processing

Pittsburgh, PA, USA
September 17-21, 2006

Data-Driven Design of Front-End Filter Bank for Lombard Speech Recognition

Hynek Boril, Petr Fousek, Petr Pollák

Czech Technical University in Prague, Czech Republic

Adverse environments not only corrupt speech signal by additive and convolutional noises, which can be successfully addressed by a number of suppression algorithms, but also affect the way how speech is produced. Speech production variations introduced by a speaker in reaction to a noisy background (Lombard effect) may result in a severe degradation of automatic speech recognition. This paper contributes to the solution of Lombard speech recognition issue by providing a robust filter bank for use in front-ends. It is shown that cepstral features derived from the proposed filter bank significantly outperform conventional cepstral features.

Full Paper

Bibliographic reference.  Boril, Hynek / Fousek, Petr / Pollák, Petr (2006): "Data-driven design of front-end filter bank for Lombard speech recognition", In INTERSPEECH-2006, paper 1803-Mon2BuP.10.