Abstract
The analysis of mobile phone speech recordings can play an important role in criminal trials. However it may be erroneously assumed that all mobile phone technologies, such as the Global System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA), are similar in their potential impact on the speech signal. In fact these technologies differ significantly in their design and internal operation. This study investigates the impact of an important aspect of these networks, namely Frame Loss (FL), on the results of a forensic voice comparison undertaken using a Bayesian likelihood ratio framework. For both networks, whenever a frame is lost or irrecoverably corrupted, it is synthetically replaced at the receiving end using a history of past good speech frames. Sophisticated mechanisms have been put in place to minimize any resulting artefacts in the recovered speech. In terms of accuracy, FL with GSMcoded speech is shown to worsen same-speaker comparisons, but improve different-speaker comparisons. In terms of precision, FL negatively impacts both sets of comparisons. With CDMA-coded speech, FL is shown to negatively impact the accuracy of both same- and different-speaker comparisons. However, surprisingly, FL is shown to improve the precision of both sets.
Highlights
Mobile phone recordings are often used as evidence in courts of law
In this paper we have presented the impact of Frame Loss (FL) on forensic voice comparison (FVC) for speech transmitted through two major mobile phone networks: Global System for Mobile Communications (GSM) and Code Division Multiple Access (CDMA)
The GSM and CDMA mobile phone networks are fundamentally different in their design and implementation and this necessarily translates into differences in the characteristics of the speech they produce and in the subsequent impact of these differences on FVC
Summary
Mobile phone recordings are often used as evidence in courts of law. Analysis of such recordings using a range of forensic voice comparison (FVC) techniques can assist the court in establishing the guilt or innocence of a suspect. Forensic speech scientists when undertaking such analysis may erroneously assume that all mobile phone networks impact the speech signal in a similar manner. There are three key aspects of these networks which can directly impact the speech signal and the outcome of a FVC analysis: (i) dynamic rate coding (DRC), (ii) strategies for handling lost or corrupted frames (FL), and (iii) strategies for overcoming the effects of background noise at the transmitting end (BN). This paper directly follows on from that work and examines the 2nd factor, the impact of FL in these two networks
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