Single-sided objective speech intelligibility assessment based on Sparse signal representation

Transcription of speech signals, originating from a lawful interception, is particularly important in the forensic phonetics framework. These signals are often degraded and the transcript may not replicate what was actually pronounced. In the absence of the clean signal, the only way to estimate the level of accuracy that can be obtained in the transcription is to develop an objective methodology for intelligibility measurements. In this paper a method based on the Normalized Spectrum Envelope (NSE) and Sparse Non-negative Matrix Factorization (SNMF) is proposed to evaluate the signal intelligibility. The approaches are tested with three different noise types and the results are compared with the speech intelligibility scores measured by subjective tests. The results of the experiments show a high correlation between objective measurements and subjective evaluations. Therefore, the proposed methodology can be successfully used in order to establish whether a given intercepted signal can be transcribed with sufficient reliability.