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Ferrer, L.; Nandwana, M.K.; McLaren, M.; Castan, D.; Lawson, A. "Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option" (2019) IEEE/ACM Transactions on Audio Speech and Language Processing. 27(1):140-153
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Abstract:

The output scores of most of the speaker recognition systems are not directly interpretable as stand-alone values. For this reason, a calibration step is usually performed on the scores to convert them into proper likelihood ratios, which have a clear probabilistic interpretation. The standard calibration approach transforms the system scores using a linear function trained using data selected to closely match the evaluation conditions. This selection, though, is not feasible when the evaluation conditions are unknown. In previous work, we proposed a calibration approach for this scenario called trial-based calibration (TBC). TBC trains a separate calibration model for each test trial using data that is dynamically selected from a candidate training set to match the conditions of the trial. In this work, we extend the TBC method, proposing: 1) a new similarity metric for selecting training data that result in significant gains over the one proposed in the original work; 2) a new option that enables the system to reject a trial when not enough matched data are available for training the calibration model; and 3) the use of regularization to improve the robustness of the calibration models trained for each trial. We test the proposed algorithms on a development set composed of several conditions and on the Federal Bureau of Investigation multi-condition speaker recognition dataset, and we demonstrate that the proposed approach reduces calibration loss to values close to 0 for most of the conditions when matched calibration data are available for selection, and that it can reject most of the trials for which relevant calibration data are unavailable. © 2014 IEEE.

Registro:

Documento: Artículo
Título:Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option
Autor:Ferrer, L.; Nandwana, M.K.; McLaren, M.; Castan, D.; Lawson, A.
Filiación:Instituto de Investigación en Ciencias de la Computación, Consejo Nacional de Investigaciones Científicas y Técnicas, Universidad de Buenos Aires, Buenos Aires, B105, Argentina
Speech Technology and Research Laboratory, SRI International, Menlo Park, CA 94025, United States
Palabras clave:forensic voice comparison; Speaker recognition; trial-based calibration; Calibration; Data structures; Logistics; Mathematical transformations; Personnel training; Statistical tests; Computational model; Forensic voice comparisons; Forensics; Probabilistic interpretation; Similarity metrics; Speaker recognition; Speaker recognition system; Standard calibration; Speech recognition
Año:2019
Volumen:27
Número:1
Página de inicio:140
Página de fin:153
DOI: http://dx.doi.org/10.1109/TASLP.2018.2875794
Título revista:IEEE/ACM Transactions on Audio Speech and Language Processing
Título revista abreviado:IEEE ACM Trans. Audio Speech Lang. Process.
ISSN:23299290
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_23299290_v27_n1_p140_Ferrer

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Citas:

---------- APA ----------
Ferrer, L., Nandwana, M.K., McLaren, M., Castan, D. & Lawson, A. (2019) . Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option. IEEE/ACM Transactions on Audio Speech and Language Processing, 27(1), 140-153.
http://dx.doi.org/10.1109/TASLP.2018.2875794
---------- CHICAGO ----------
Ferrer, L., Nandwana, M.K., McLaren, M., Castan, D., Lawson, A. "Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option" . IEEE/ACM Transactions on Audio Speech and Language Processing 27, no. 1 (2019) : 140-153.
http://dx.doi.org/10.1109/TASLP.2018.2875794
---------- MLA ----------
Ferrer, L., Nandwana, M.K., McLaren, M., Castan, D., Lawson, A. "Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option" . IEEE/ACM Transactions on Audio Speech and Language Processing, vol. 27, no. 1, 2019, pp. 140-153.
http://dx.doi.org/10.1109/TASLP.2018.2875794
---------- VANCOUVER ----------
Ferrer, L., Nandwana, M.K., McLaren, M., Castan, D., Lawson, A. Toward Fail-Safe Speaker Recognition: Trial-Based Calibration with a Reject Option. IEEE ACM Trans. Audio Speech Lang. Process. 2019;27(1):140-153.
http://dx.doi.org/10.1109/TASLP.2018.2875794