| Publication Type |
Conference Paper |
| Authors |
Mirco Rossi, Oliver Amft, Martin Kusserow, Gerhard Tröster |
| Title |
Collaborative Real-Time Speaker Identification for Wearable Systems |
| Abstract |
We present an unsupervised speaker identification system for personal annotations of conversations and meetings. The system dynamically learns new speakers and recognizes already known speakers using one audio channel and speech-independent modeling. Multiple personal systems could collaborate in robust unsupervised speaker identification and online learning. The system was optimized for real-time operation on a DSP system that can be worn during daily activities. The system was evaluated on the freely available 24-speaker Augmented Multiparty Interaction dataset. For 5s recognition time, the system achieves 81% recognition rate. Collaboration between four identification systems resulted in a performance increase of up to 17%, however even two collaborating systems yield an performance improvement. A prototypical wearable DSP implementation could continuously operate for more than 8hours from a 4.1Ah battery. |
| Date |
2010 |
| Proceedings Title |
PerCom 2010: Proceedings of the 8th Annual IEEE International Conference on Pervasive Computing and Communications |
| Publisher |
IEEE |
| Pages |
180–189 |
| DOI |
10.1109/PERCOM.2010.5466976 |
| Extra |
Acceptance rate: 12% |
| Full Text |
PDF |
