D-vector based speaker verification system using Raw Waveform CNN
Jeeweon Jung, Heesoo Heo, Ilho Yang, Sunghyun Yoon, Hyejin Shim, Hajin Yu
Available Online December 2017.
- https://doi.org/10.2991/anit-17.2018.21How to use a DOI?
- d-vector, speaker verification, raw-audio-CNN
- In this paper, we propose a d-vector based speaker verification system in which raw-audio-CNN is used as a d-vector extractor instead of a conventional multi-layer perceptron. Because raw-audio-CNN takes raw wave signals as input, traditional acoustic feature extracting methods such as mel-frequency cepstral coefficient and mel-filterbank features are no longer needed. The results of experiments conducted show that raw-audio-CNN can successfully perform functions carried out by traditional acoustic feature extracting methods and outperforms traditional d-vector systems that utilize standard multi-layer perceptron with acoustic features.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Jeeweon Jung AU - Heesoo Heo AU - Ilho Yang AU - Sunghyun Yoon AU - Hyejin Shim AU - Hajin Yu PY - 2017/12 DA - 2017/12 TI - D-vector based speaker verification system using Raw Waveform CNN BT - Proceedings of the 2017 International Seminar on Artificial Intelligence, Networking and Information Technology (ANIT 2017) PB - Atlantis Press SP - 126 EP - 131 SN - 1951-6851 UR - https://doi.org/10.2991/anit-17.2018.21 DO - https://doi.org/10.2991/anit-17.2018.21 ID - Jung2017/12 ER -