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Scritto da  Giovedì, 20 Marzo 2014 09:22

 

SINGLE-SIDED OBJECTIVE SPEECH INTELLIGIBILITY ASSESSMENT BASED ON SPARSE SIGNAL REPRESENTATION

Giovanni Costantini, Massimiliano Todisco, Renzo Perfetti, Andrea Paoloni, Giovanni Saggio

2012 IEEE INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING, SEPT. 23–26, 2012, SANTANDER, SPAIN

 

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.





Letto 30935 volte Ultima modifica il Venerdì, 21 Marzo 2014 08:50

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