Events and Challenges

Activities

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Event

Yamagishi Lab Events

Our lab regularly organizes events and seminars for academic researchers. Below are some examples. These workshops facilitate sharing specialized knowledge, acquiring practical skills, and in-depth discussions on research topics, encouraging collaboration and mutual learning among members. In addition, by engaging with external experts, we provide opportunities for new ideas and collaborative projects to emerge.

  • PhD Thesis Presentations at the Yamagishi Lab

    Yamagishi Lab PhD Defenses

  • VoicePersonae and ASVspoof 2023 Joint Workshop

    Joint Workshop of VoicePersonae and ASVspoof 2023

    We held a joint workshop of the VoicePersonae Project and the ASVspoof Challenge in Hitotsubashi, Tokyo, Japan.

Challenge

About Challenges

Our laboratory collaborates with other universities and research institutions to jointly organize challenges where researchers compete to achieve the best performance on specific machine learning tasks using shared datasets. These challenges provide a platform for researchers to exchange techniques and insights, helping to accelerate progress in their fields. Following the challenges, we also organize special sessions at international conferences.

  • ASVspoof 5

    ASVspoof5

    This is the fifth edition of the ASVspoof challenge series, which focuses on spoofing attacks against speaker recognition systems and detecting deepfakes. Here, we provide large-scale datasets along with baseline methods.

  • VoicePrivacy Challenge

    VoicePrivacy Challenge

    The VoicePrivacy Initiative is a challenge focused on speaker anonymization technology for voice privacy protection. It provides datasets, baseline systems, and evaluation metrics for speaker anonymization experiments.

  • VoiceMOS

    VoiceMOS

    The VoiceMOS Challenge is a challenge focused on the task of automatically predicting the subjective rating value, Mean Opinion Score (MOS), from speech. We provide a dataset, baseline methods, and evaluation metrics for MOS prediction experiments.