3260 papers • 126 benchmarks • 313 datasets
This task has no description! Would you like to contribute one?
(Image credit: Papersgraph)
These leaderboards are used to track progress in speaker-verification
No benchmarks available.
Use these libraries to find speaker-verification models and implementations
No datasets available.
No subtasks available.
A data-driven, integrated approach to speaker verification, which maps a test utterance and a few reference utterances directly to a single score for verification and jointly optimizes the system's components using the same evaluation protocol and metric as at test time.
This paper analyzes the usage of attention mechanisms to the problem of sequence summarization in the authors' end-to-end text-dependent speaker recognition system and shows that attention-based models can improves the Equal Error Rate (EER) of the speaker verification system by relatively 14% compared to their non-attention LSTM baseline model.
Adding a benchmark result helps the community track progress.