{"action":"opened","issue":{"url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/7124","repository_url":"https://api.github.com/repos/ikedaosushi/tech-news","labels_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/7124/labels{/name}","comments_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/7124/comments","events_url":"https://api.github.com/repos/ikedaosushi/tech-news/issues/7124/events","html_url":"https://github.com/ikedaosushi/tech-news/issues/7124","id":358916208,"node_id":"MDU6SXNzdWUzNTg5MTYyMDg=","number":7124,"title":"[1808.00158v2] Speaker Recognition from Raw Waveform with SincNet","user":{"login":"ikedaosushi","id":4068610,"node_id":"MDQ6VXNlcjQwNjg2MTA=","avatar_url":"https://avatars1.githubusercontent.com/u/4068610?v=4","gravatar_id":"","url":"https://api.github.com/users/ikedaosushi","html_url":"https://github.com/ikedaosushi","followers_url":"https://api.github.com/users/ikedaosushi/followers","following_url":"https://api.github.com/users/ikedaosushi/following{/other_user}","gists_url":"https://api.github.com/users/ikedaosushi/gists{/gist_id}","starred_url":"https://api.github.com/users/ikedaosushi/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ikedaosushi/subscriptions","organizations_url":"https://api.github.com/users/ikedaosushi/orgs","repos_url":"https://api.github.com/users/ikedaosushi/repos","events_url":"https://api.github.com/users/ikedaosushi/events{/privacy}","received_events_url":"https://api.github.com/users/ikedaosushi/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-09-11T07:13:35Z","updated_at":"2018-09-11T07:13:35Z","closed_at":null,"author_association":"OWNER","body":"[1808.00158v2] Speaker Recognition from Raw Waveform with SincNet<br>\nFull-text links: Download: (license) Bookmark (what is this?) Title: Speaker Recognition from Raw Waveform with SincNet Authors: Mirco Ravanelli, Yoshua Bengio v1), last revised 9 Sep 2018 (this version, v2)) Abstract: Deep learning is progressively gaining popularity as a viable<br>\nhttps://ift.tt/2x3isOJ"}}
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