The 2020 Personalized Voice Trigger Challenge: Open Database, Evaluation Metrics and the Baseline Systems
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Abstract (arXiv)
The 2020 Personalized Voice Trigger Challenge (PVTC2020) addresses two different research problems a unified setup: joint wake-up word detection with speaker verification on close-talking single microphone data and far-field multi-channel microphone array data. Specially, the second task poses an additional cross-channel matching challenge on top of the far-field condition. To simulate the real-life application scenario, the enrollment utterances are recorded from close-talking cell-phone only, while the test utterances are recorded from both the close-talking cell-phone and the far-field microphone arrays. This paper introduces our challenge setup and the released database as well as the evaluation metrics. In addition, we present a joint end-to-end neural network baseline system trained with the proposed database for speaker-dependent wake-up word detection. Results show that the cost calculated from the miss rate and the false alarm rate, can reach 0.37 in the close-talking single microphone task and 0.31 in the far-field microphone array task. The official website and the open-source baseline system have been released.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Jan 2021.
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Citing papers per year: 2021: 3; 2022: 1.
4 papers.
- 2021The NPU System for the 2020 Personalized Voice Trigger Challengecited by 2
- 2021Auto-KWS 2021 Challenge: Task, Datasets, and Baselinescited by 2
- 2021Binary Neural Network for Speaker Verificationcited by 2
- 2022Improving Voice Trigger Detection with Metric Learningcited by 1
- 2022Improving Voice Trigger Detection with Metric Learning5 Apr 2022
- 2021Binary Neural Network for Speaker Verification6 Apr 2021
- 2021Auto-KWS 2021 Challenge: Task, Datasets, and Baselines31 Mar 2021
- 2021The NPU System for the 2020 Personalized Voice Trigger Challenge26 Feb 2021