Graduate School and Research Center in Digital Sciences

Enhanced low-latency speaker spotting using selective cluster enrichment

Patino, José. Delgado, Hector; Evans, Nicholas

BIOSIG 2018, 17th International Conference of the Biometrics Special Interest Group, 26-29 September 2018, Darmstadt, Germany

Low-latency speaker spotting (LLSS) calls for the rapid detection of known speakers within multi-speaker audio streams. While previous work showed the potential to develop efficient LLSS solutions by combining speaker diarization and speaker detection within an online processing framework, it failed to move significantly beyond the traditional definition of diarization. This paper shows that the latter needs rethinking and that a diarization sub-system tailored to the end application, rather than to the minimisation of the diarization error rate, can improve LLSS performance. The proposed selective cluster enrichment algorithm is used to guide the diarization system to better model segments within a multi-speaker audio stream and hence detect more reliably a given target speaker. The LLSS solution reported in this paper shows that target speakers can be detected with a 16% equal error rate after having been active in multi-speaker audio streams for only 15 seconds.

Document Doi Bibtex

Title:Enhanced low-latency speaker spotting using selective cluster enrichment
Keywords:low-latency speaker spotting, speaker detection, speaker diarization
Department:Digital Security
Eurecom ref:5702
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Bibtex: @inproceedings{EURECOM+5702, doi = {}, year = {2018}, title = {{E}nhanced low-latency speaker spotting using selective cluster enrichment}, author = {{P}atino, {J}os{\'e}. {D}elgado, {H}ector and {E}vans, {N}icholas}, booktitle = {{BIOSIG} 2018, 17th {I}nternational {C}onference of the {B}iometrics {S}pecial {I}nterest {G}roup, 26-29 {S}eptember 2018, {D}armstadt, {G}ermany }, address = {{D}armstadt, {GERMANY}}, month = {09}, url = {} }
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