Design and collection of Czech Lombard speech database

In this paper, design, collection and parameters of newly proposed Czech Lombard Speech Database (CLSD) are presented. The database focuses on analysis and modeling of Lombard effect to achieve robust speech recognition improvement. The CLSD consists of neutral speech and speech produced in various types of simulated noisy background. In comparison to available databases dealing with Lombard effect, an extensive set of utterances containing phonetically rich words and sentences was chosen to cover the whole phoneme vocabulary of the language. For the purposes of Lombard speech recording, usual ‘noisy headphones configuration’ was improved by addition of an operator qualifying utterance intelligibility while hearing the same noise mixed with speaker’s voice of intensity lowered according to the selected virtual distance. This scenario motivated speakers to react more to the noise background. The CLSD currently consists of 26 speakers.

[1]  Yung-Hwan Oh,et al.  Lombard effect compensation and noise suppression for noisy Lombard speech recognition , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[2]  John H. L. Hansen,et al.  Classification of speech under stress using target driven features , 1996, Speech Commun..

[3]  Kazuya Takeda,et al.  Variability of Lombard effects under different noise conditions , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[4]  Jonas Beskow,et al.  Wavesurfer - an open source speech tool , 2000, INTERSPEECH.

[5]  Pavel Sovka,et al.  Czech language database of car speech and environmental noise , 1999, EUROSPEECH.

[6]  F. Harris.  On the use of windows for harmonic analysis with the discrete Fourier transform , 1978, Proceedings of the IEEE.

[7]  John H. L. Hansen,et al.  Analysis and compensation of speech under stress and noise for environmental robustness in speech recognition , 1996, Speech Commun..