The audio bandwidth of digital landline and mobile telephone networks is still mostly restricted to 200 Hz to 3.4 kHz. This is due to compatibility requirements during the transition phase from analogue to digital transmission technology. The resulting characteristic "telephone speech" is widely accepted, but the intelligibility of syllables is only 91%.

Meanwhile, improved coding standards for so-called “HD voice” or “Wideband Speech” have been developed which are gradually being introduced into the networks. They support an audio frequency bandwidth of 50 Hz to 7.0 kHz with significantly increased audio quality and speech intelligibility. For a very long time however, new HD-telephones and old narrowband telephones have to co-exist. If an HD-terminal is connected over a narrowband link to an old telephone, the improved coding scheme cannot be used.

In this thesis, signal processing concepts are developed for improving audio quality and intelligibility of narrowband speech by artificial bandwidth extension (ABWE). These algorithms can be applied in the HD terminals or in the network, to transform narrowband speech to HD voice. Based on the source-filter model of speech production and a priori knowledge of the characteristics of speech signals, the missing frequency components between 3.4 kHz and 7 kHz are reconstructed. In comparison to the state-of-the-art ABWE approaches, the main contributions are:

• new concepts of estimating the wideband spectral envelope, e.g., in terms of the model filter by interpolation in the acoustic tube domain

• algorithms for spectral extension of the excitation signal

• new insights concerning the relative importance of the excitation, the temporal envelope and the spectral envelope

• remarkable improvements of the audio quality • significant low computational complexity

• efficient and effective training and estimation algorithms The improvements are verified by objective evaluation and subjective listening tests.