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- W4312768031 abstract "Speech endpoint detection is the crucial part of fixed phrase speaker verification as the performance of the system is largely depends on the proper start and terminus point identification. In this paper, we have analyzed the effect of endpoint detection on fixed phrase speaker verification. For this experimental study, we have selected three endpoint detection techniques from the literature. These are energy-based voice activity detection (VAD), glottal activity detection (GAD), and pitch and energy-based detection (PED). Our fixed phrase speaker verification model is developed using Mel Frequency Cepstral Coefficients (MFCC) features and for template matching dynamic time warping (DTW) is used. The experimentation for speaker matching is done by speaker-specific threshold and cohort speaker-based approach. We have performed our analysis on the RSR2015 database, which was collected in a controlled environment, and the NITS database that was recorded in a real-life scenario. The result of our experimental evaluation resembles that the PED gives better performance compared to VAD and GAD. An average improvement of 5.2% and 3.9% in Equal Error Rate (EER) is achieved with PED in comparison to VAD and GAD, respectively." @default.
- W4312768031 created "2023-01-05" @default.
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- W4312768031 date "2022-01-01" @default.
- W4312768031 modified "2023-10-18" @default.
- W4312768031 title "Effect of End Point Detection on Fixed Phrase Speaker Verification" @default.
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- W4312768031 doi "https://doi.org/10.1007/978-981-19-4300-3_30" @default.
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