2021/01/06 by Yan Jia, Jia, Yan, Xingming Wang +11 · 2 citations
Computer Science · Engineering · #Audio and Speech Processing (eess.AS) #FOS: Electrical engineering #Music and Audio Processing #Speech Recognition and Synthesis #Speech and Audio Processing #eess.AS #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2101.01935
arxiv created 2021/01/06 · openalex publication_date 2021/01/06 · arxiv updated 2021/01/07 · openalex created_date 2021/01/18 · openalex updated_date 2026/07/28
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.