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.
Type:
Conférence
City:
Darmstadt
Date:
2018-09-26
Department:
Sécurité numérique
Eurecom Ref:
5702
Copyright:
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