Comparison of two speech content authentication approaches

Speech content authentication, which is also called speech content integrity or tamper detection, protects the integrity of speech contents instead of the bitstream itself. In this work, two major approaches for flexible speech authentication are presented and compared. The first scheme is based on content feature extraction that is integrated with CELP speech coders to minimize the total computational cost. Speech features relevant to semantic meaning are extracted, encrypted and attached as the header information. The second method embeds fragile watermarks into the speech signal in the frequency domain. If the speech signal is tampered, the secret watermark sequence is also modified. The receiver detects the fragile watermark from received data and compares it to the original secret sequence. These two approaches are compared in terms of computational complexity, false detection rate, and tolerance to mis-synchronization and content preserving operations. It is shown that each approach has its own merits and shortcomings.