A Unified Framework for Speaker and Utterance Verification

Tianchi Liu, Maulik Madhavi, Rohan Kumar Das, Haizhou Li

Speaker and utterance verification are two tasks that co-exist in text-dependent speaker verification (SV), where a phrase of the same lexical information is spoken during train and test sessions. The conventional approaches mostly verify the speaker and the utterance separately using two models. While there are studies on joint modeling of speaker and utterance, it is always desirable to have a common framework that performs both speaker and utterance verification to access the intended service. To this end, we propose a unified framework that deals with both objectives and the trade-off between the two. The unified framework is based on long short term memory network trained using both speaker and utterance information. We use Part I of RSR2015 database for the studies in this work. We show that the unified framework not only demonstrates competitive SV performance, but also provides a solution for a system to address different levels of security need.

 DOI: 10.21437/Interspeech.2019-1994

Cite as: Liu, T., Madhavi, M., Das, R.K., Li, H. (2019) A Unified Framework for Speaker and Utterance Verification. Proc. Interspeech 2019, 4320-4324, DOI: 10.21437/Interspeech.2019-1994.

  author={Tianchi Liu and Maulik Madhavi and Rohan Kumar Das and Haizhou Li},
  title={{A Unified Framework for Speaker and Utterance Verification}},
  booktitle={Proc. Interspeech 2019},