Text-Dependent Speaker Verification Using SSI-DNN Trained on Short Utterance
Kentaro Kameda, Satoru Tsuge, Shingo Kuroiwa, Yasuo Horiuchi, Masafumi Nishida · 2024
To enhance speaker verification for short utterances, we have developed a Same Speaker Identification Deep Neural Network (SSI-DNN). This network identifies whether two utterances are uttered by the same speaker with greater accuracy by focusing on the same texts. In this paper, we extend the detection target of the SSI-DNN from monosyllabic utterances to word utterances to improve the speaker recognition performance. Experimental results showed that the SSI-DNN trained on word utterances achieved an EER of 0.1% to 2.8%. These results indicated that the SSI-DNN outperformed the x-vector-based speaker verification method, which is a representative speaker verification method.