Digital watermarking of biometric speech references: impact to the EER system performance

Abstract

The evaluation of digital watermarks has grown into an important research area. The usage of profiles for application oriented evaluation provides an efficient and aimed strategy to evaluate and compare watermarking schemes according to a predefined watermark parameter setting. Based on first evaluations in [5, 16], in this paper, we present a new application profile (called Biometrics) and exemplary test results for audio watermarking evaluations. Therefore, we combine digital watermark evaluation and a biometric authentication system. This application scenario is as follows: Audio watermarking schemes are used to embed metadata into the speech reference data of the biometric speaker recognition system. Metadata in our context may consist of feature template representations complementary to the speech modality, such as iris codes or biometric hashes, ancillary information about the social, cultural or biological context of the owner of the biometric data or technical details of the sensor. As during watermark embedding the cover signal is changed, the test results show how different watermarking schemes affect the biometric error rates and speech performance of the biometric system depending on the embedding capacity and embedding transparency. Therefore, the biometric error rates are measured for each watermarking scheme, the effect of embedding is shown, and its influence is analyzed. The transparency of an embedding function is manly measured with subjective or objective tests. In this paper, we introduce a new objective test called Biometric Difference Grade (BDG) to evaluate the quality for biometric speech signal modifications on the example of four audio watermarking algorithms.