Conversation detection and speaker segmentation in privacy-sensitive situated speech data
| Autor: | Jeff A. Bilmes, Tanzeem Choudhury, Danny Wyatt |
|---|---|
| Rok vydání: | 2007 |
| Předmět: |
Computer science
business.industry Speech recognition media_common.quotation_subject Intelligibility (communication) computer.software_genre Speaker recognition Speaker diarisation Dynamics (music) Situated Conversation Segmentation Artificial intelligence business computer Natural language processing media_common |
| Zdroj: | INTERSPEECH |
| DOI: | 10.21437/interspeech.2007-256 |
| Popis: | We present privacy-sensitive methods for (1) automatically finding multi-person conversations in spontaneous, situated speech data and (2) segmenting those conversations into speaker turns. The methods protect privacy through a feature set that is rich enough to capture conversational styles and dynamics, but not sufficient for reconstructing intelligible speech. Experimental results show that the conversation finding method outperforms earlier approaches and that the speaker segmentation method is a significant improvement to the only other known privacy-sensitive method for speaker segmentation. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|