A “microscopic” model of phoneme recognition, which includes an auditory model and a simple speech recognizer, is adapted to model the recognition of single words within whole German sentences. “Microscopic” in terms of this model is defined twofold, first, as analyzing the particular spectro-temporal structure of the speech waveforms, and second, as basing the recognition of whole sentences on the recognition of single words. This approach is evaluated on a large database of speech recognition results from normal-hearing and sensorineural hearing-impaired listeners. Individual audiometric thresholds are accounted for by implementing a spectrally-shaped hearing threshold simulating noise. Furthermore, a comparative challenge between the microscopic model and the “macroscopic” Speech Intelligibility Index (SII) is performed using the same listeners’ data. The results are that both models show similar correlations of modeled Speech Reception Thresholds (SRTs) to observed SRTs.