{"action":"created","issue":{"url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/13","repository_url":"https://api.github.com/repos/philipperemy/deep-speaker","labels_url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/13/labels{/name}","comments_url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/13/comments","events_url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/13/events","html_url":"https://github.com/philipperemy/deep-speaker/issues/13","id":280909919,"number":13,"title":"Trained model produces near-identical outputs for different inputs?","user":{"login":"linhdvu14","id":13968867,"avatar_url":"https://avatars1.githubusercontent.com/u/13968867?v=4","gravatar_id":"","url":"https://api.github.com/users/linhdvu14","html_url":"https://github.com/linhdvu14","followers_url":"https://api.github.com/users/linhdvu14/followers","following_url":"https://api.github.com/users/linhdvu14/following{/other_user}","gists_url":"https://api.github.com/users/linhdvu14/gists{/gist_id}","starred_url":"https://api.github.com/users/linhdvu14/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/linhdvu14/subscriptions","organizations_url":"https://api.github.com/users/linhdvu14/orgs","repos_url":"https://api.github.com/users/linhdvu14/repos","events_url":"https://api.github.com/users/linhdvu14/events{/privacy}","received_events_url":"https://api.github.com/users/linhdvu14/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":9,"created_at":"2017-12-11T06:45:05Z","updated_at":"2018-04-11T09:05:06Z","closed_at":null,"author_association":"CONTRIBUTOR","body":"As title. I noticed the trained model produces near-identical embeddings for different input audios (even randomly generated values). Is anyone having this issue?\r\n\r\nIf it helps, I'm training with\r\n- LibriSpeech dev-clean dataset: http://www.openslr.org/12/\r\n- SAMPLE_RATE = 16000\r\n- BATCH_NUM_TRIPLETS = 21\r\n- TRUNCATE_SOUND_FIRST_SECONDS = 3\r\n- Loss = 0.10225 when I stopped training\r\n\r\nI've tried a few different datasets/settings and had the same results.\r\n\r\nProbably related to #9 . Somehow the model decides the best way to go is make all embeddings the same, hence loss = margin..."},"comment":{"url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/comments/380381564","html_url":"https://github.com/philipperemy/deep-speaker/issues/13#issuecomment-380381564","issue_url":"https://api.github.com/repos/philipperemy/deep-speaker/issues/13","id":380381564,"user":{"login":"philipperemy","id":4516927,"avatar_url":"https://avatars1.githubusercontent.com/u/4516927?v=4","gravatar_id":"","url":"https://api.github.com/users/philipperemy","html_url":"https://github.com/philipperemy","followers_url":"https://api.github.com/users/philipperemy/followers","following_url":"https://api.github.com/users/philipperemy/following{/other_user}","gists_url":"https://api.github.com/users/philipperemy/gists{/gist_id}","starred_url":"https://api.github.com/users/philipperemy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/philipperemy/subscriptions","organizations_url":"https://api.github.com/users/philipperemy/orgs","repos_url":"https://api.github.com/users/philipperemy/repos","events_url":"https://api.github.com/users/philipperemy/events{/privacy}","received_events_url":"https://api.github.com/users/philipperemy/received_events","type":"User","site_admin":false},"created_at":"2018-04-11T09:05:06Z","updated_at":"2018-04-11T09:05:06Z","author_association":"OWNER","body":"@Curisan great I think we're moving to the right direction :)"}}
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