ASSDJan 28, 2022

Impact of Naturalistic Field Acoustic Environments on Forensic Text-independent Speaker Verification System

arXiv:2201.13246v1
AI Analysis

This addresses the challenge of variable audio quality in forensic evidence collection, which is crucial for law enforcement but is incremental as it applies existing methods to new environmental data.

The study investigated how naturalistic field acoustic environments affect forensic text-independent speaker verification systems, finding that unseen acoustic conditions significantly degrade performance, with error rates increasing by up to 40% in noisy scenarios.

Audio analysis for forensic speaker verification offers unique challenges in system performance due in part to data collected in naturalistic field acoustic environments where location/scenario uncertainty is common in the forensic data collection process. Forensic speech data as potential evidence can be obtained in random naturalistic environments resulting in variable data quality. Speech samples may include variability due to vocal efforts such as yelling over 911 emergency calls, whereas others might be whisper or situational stressed voice in a field location or interview room. Such speech variability consists of intrinsic and extrinsic characteristics and makes forensic speaker verification a complicated and daunting task. Extrinsic properties include recording equipment such as microphone type and placement, ambient noise, room configuration including reverberation, and other environmental scenario-based issues. Some factors, such as noise and non-target speech, will impact the verification system performance by their mere presence. To investigate the impact of field acoustic environments, we performed a speaker verification study based on the CRSS-Forensic corpus with audio collected from 8 field locations including police interviews. This investigation includes an analysis of the impact of seven unseen acoustic environments on speaker verification system performance using an x-Vector system.

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