This paper presents an analysis of the KPT system for the 2022 NIST Language Recognition Evaluation. The KPT submission focuses on the fixed training condition where only specific speech data can be used to develop all the modules and auxiliary systems used to build the language recognizer. Our solution consists of several sub-systems based on different neural network front-ends and a common back-end for classification and fusion. The goal of each front-end is to extract language-related embeddings. Gaussian linear models are used to classify the embeddings of each front-end, followed by multi-class logistic regression to calibrate and fuse the different sub-systems. Experimental results from the NIST LRE 2022 evaluation task show that our approach achieves competitive performance.

Sarni S., Cumani S., Siniscalchi S.M., Bottino A. (2023). Description and analysis of the KPT system for NIST Language Recognition Evaluation 2022. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2023 (pp. 1933-1937). International Speech Communication Association [10.21437/Interspeech.2023-155].

Description and analysis of the KPT system for NIST Language Recognition Evaluation 2022

Siniscalchi S. M.;Bottino A.
2023-01-01

Abstract

This paper presents an analysis of the KPT system for the 2022 NIST Language Recognition Evaluation. The KPT submission focuses on the fixed training condition where only specific speech data can be used to develop all the modules and auxiliary systems used to build the language recognizer. Our solution consists of several sub-systems based on different neural network front-ends and a common back-end for classification and fusion. The goal of each front-end is to extract language-related embeddings. Gaussian linear models are used to classify the embeddings of each front-end, followed by multi-class logistic regression to calibrate and fuse the different sub-systems. Experimental results from the NIST LRE 2022 evaluation task show that our approach achieves competitive performance.
2023
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
Sarni S., Cumani S., Siniscalchi S.M., Bottino A. (2023). Description and analysis of the KPT system for NIST Language Recognition Evaluation 2022. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2023 (pp. 1933-1937). International Speech Communication Association [10.21437/Interspeech.2023-155].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/637522
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