Acoustic compression in Zoom audio does not compromise voice recognition performance

Human voice recognition over telephone channels typically yields lower accuracy when compared to audio recorded in a studio environment with higher quality. Here, we investigated the extent to which audio in video conferencing, subject to various lossy compression mechanisms, affects human voice recognition performance. Voice recognition performance was tested in an old–new recognition task under three audio conditions (telephone, Zoom, studio) across all matched (familiarization and test with same audio condition) and mismatched combinations (familiarization and test with different audio conditions). Participants were familiarized with female voices presented in either studio-quality (N = 22), Zoom-quality (N = 21), or telephone-quality (N = 20) stimuli. Subsequently, all listeners performed an identical voice recognition test containing a balanced stimulus set from all three conditions. Results revealed that voice recognition performance (dʹ) in Zoom audio was not significantly different to studio audio but both in Zoom and studio audio listeners performed significantly better compared to telephone audio. This suggests that signal processing of the speech codec used by Zoom provides equally relevant information in terms of voice recognition compared to studio audio. Interestingly, listeners familiarized with voices via Zoom audio showed a trend towards a better recognition performance in the test (p = 0.056) compared to listeners familiarized with studio audio. We discuss future directions according to which a possible advantage of Zoom audio for voice recognition might be related to some of the speech coding mechanisms used by Zoom

The Effect Of Acoustic Variability On Automatic Speaker Recognition Systems

This thesis examines the influence of acoustic variability on automatic speaker recognition systems (ASRs) with three aims. i. To measure ASR performance under 5 commonly encountered acoustic conditions; ii. To contribute towards ASR system development with the provision of new research data; iii. To assess ASR suitability for forensic speaker comparison (FSC) application and investigative/pre-forensic use. The thesis begins with a literature review and explanation of relevant technical terms. Five categories of research experiments then examine ASR performance, reflective of conditions influencing speech quantity (inhibitors) and speech quality (contaminants), acknowledging quality often influences quantity. Experiments pertain to: net speech duration, signal to noise ratio (SNR), reverberation, frequency bandwidth and transcoding (codecs). The ASR system is placed under scrutiny with examination of settings and optimum conditions (e.g. matched/unmatched test audio and speaker models). Output is examined in relation to baseline performance and metrics assist in informing if ASRs should be applied to suboptimal audio recordings. Results indicate that modern ASRs are relatively resilient to low and moderate levels of the acoustic contaminants and inhibitors examined, whilst remaining sensitive to higher levels. The thesis provides discussion on issues such as the complexity and fragility of the speech signal path, speaker variability, difficulty in measuring conditions and mitigation (thresholds and settings). The application of ASRs to casework is discussed with recommendations, acknowledging the different modes of operation (e.g. investigative usage) and current UK limitations regarding presenting ASR output as evidence in criminal trials. In summary, and in the context of acoustic variability, the thesis recommends that ASRs could be applied to pre-forensic cases, accepting extraneous issues endure which require governance such as validation of method (ASR standardisation) and population data selection. However, ASRs remain unsuitable for broad forensic application with many acoustic conditions causing irrecoverable speech data loss contributing to high error rates