The DOI matches its Crossref record.
Analysis of Critical Metadata Factors for the Calibration of Speaker Recognition Systems
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Discrimination is robust independently from the dataset the system was calibrated with, but calibration itself is highly dependent on the conditions.
“The discrimination is robust independently from the dataset the system was calibrated with, but calibration itself is highly dependent on the conditions [31].”
From Calibration of score based likelihood ratio estimation in automated forensic facial image comparison (2022) · cites this paper as [31]
In speaker comparison, the effect of duration, distance, language, and gender by using a variety of datasets makes a difference in the calibration results.
“In particular, in the work of [31] the effect of duration, distance, language, and gender in speaker comparison by using a variety of datasets makes a difference in the calibration results.”
From Calibration of score based likelihood ratio estimation in automated forensic facial image comparison (2022) · cites this paper as [31]
Citations
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Sorted by citations
Calibration of score based likelihood ratio estimation in automated forensic facial image comparison
Rodriguez, A. M., Geradts, Z., & Worring, M. (2022) · Forensic Science International · doi:10.1016/j.forsciint.2022.111239 · Cited by 19
Metadata
- Authors
- Nandwana, M. K., Ferrer, L., McLaren, M., Castan, D., & Lawson, A.
- Venue
- Interspeech 2019
- Publisher
- ISCA
- Published
- 2019-09-15
- Pages
- 4325-4329
- Cited by
- 12
- References
- 0
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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