Objective Speech Intelligibility Measures Based on Speech Transmission Index for Forensic Applications

Costantini G, Paoloni A, Todisco M. Objective Speech Intelligibility Measures Based on Speech Transmission Index for Forensic Applications. In: AES Conference: 39th International Conference: Audio Forensics: Practices and Challenges. Audio Engineering Society; 2010.pp. 8-2:1-7. Available from: https://aes.org/publications/elibrary-page/?id=15496

@inproceedings{Costantini2010_15496,
  author = {Costantini, Giovanni and Paoloni, Andrea and Todisco, Massimiliano},
  title = {{Objective Speech Intelligibility Measures Based on Speech Transmission Index for Forensic Applications}},
  booktitle = {AES Conference: 39th International Conference: Audio Forensics: Practices and Challenges},
  pages = {8-2:1-7},
  url = {https://aes.org/publications/elibrary-page/?id=15496},
  year = {2010},
  month = jun,
  publisher = {Audio Engineering Society}
}

TY  - CPAPER
TI  - Objective Speech Intelligibility Measures Based on Speech Transmission Index for Forensic Applications
AU  - Costantini, Giovanni
AU  - Paoloni, Andrea
AU  - Todisco, Massimiliano
T2  - AES Conference: 39th International Conference: Audio Forensics: Practices and Challenges
SP  - 1
EP  - 7
M1  - Paper 8-2
PY  - 2010
DA  - 2010/06/06
UR  - https://aes.org/publications/elibrary-page/?id=15496
PB  - Audio Engineering Society
LA  - en
AB  - In order to decide whether the transposition of the speech originated from a lawful interception, in the written text reflect the views of those who spoke the words or only the views of the transcriber, is required to have an objective method to measure speech intelligibility. Usually, a lawful interception can have two types of distortion: the distortions that affect the speech signal itself (called speech distortion) and the distortions that affect the background noise (called noise distortion). Unfortunately, the forensic expert does not have the original clean signal, therefore, must make its assessment based on the only available signal. This paper addresses the issue by using three different objective approaches, that are the Signal-to-Noise ratio weighted with the curves "A" (S/NA), the Articulation Index (AI) and Speech Transmission Index (STI) to evaluate the signal and a corpus which is measured voice intelligibility. The approaches are tested with three different types of noise and the results were compared with the speech intelligibility scores measured by subjective tests. Measures based on STI have proven to be reliable for predicting the intelligibility in forensic applications.
ER  -