DISTBIC: a speaker-based segmentation for audio data indexing
Speech Communication - Special issue on accessing information in spoken audio
Segregation of speakers for speech recognition and speaker identification
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
On the use of dot scoring for speaker diarization
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
International Journal of Speech Technology
| Hi-index | 0.01 |
The automatic transcription of broadcast news and meetings involves the segmentation, identification and tracking of speaker turns during each session, which is known as speaker diarization. This paper presents a simple but effective approach to a slightly different task, called speaker tracking, also involving audio segmentation and speaker identification, but with a subset of known speakers, which allows to estimate speaker models and to perform identification on a segment-by-segment basis. The proposed algorithm segments the audio signal in a fully unsupervised way, by locating the most likely change points from an purely acoustic point of view. Then the available speaker data are used to estimate single-Gaussian acoustic models. Finally, speaker models are used to classify the audio segments by choosing the most likely speaker or, alternatively, the Othercategory, if none of the speakers is likely enough. Despite its simplicity, the proposed approach yielded the best performance in the speaker tracking challenge organized in November 2006 by the Spanish Network on Speech Technology.