{"action":"created","issue":{"url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/2","repository_url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn","labels_url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/2/labels{/name}","comments_url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/2/comments","events_url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/2/events","html_url":"https://github.com/ganesa90/speech-inversion-dnn/issues/2","id":334643321,"node_id":"MDU6SXNzdWUzMzQ2NDMzMjE=","number":2,"title":"What's the length of the window to produce a feature vector? ","user":{"login":"hbake001","id":32879867,"node_id":"MDQ6VXNlcjMyODc5ODY3","avatar_url":"https://avatars1.githubusercontent.com/u/32879867?v=4","gravatar_id":"","url":"https://api.github.com/users/hbake001","html_url":"https://github.com/hbake001","followers_url":"https://api.github.com/users/hbake001/followers","following_url":"https://api.github.com/users/hbake001/following{/other_user}","gists_url":"https://api.github.com/users/hbake001/gists{/gist_id}","starred_url":"https://api.github.com/users/hbake001/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/hbake001/subscriptions","organizations_url":"https://api.github.com/users/hbake001/orgs","repos_url":"https://api.github.com/users/hbake001/repos","events_url":"https://api.github.com/users/hbake001/events{/privacy}","received_events_url":"https://api.github.com/users/hbake001/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-06-21T20:22:38Z","updated_at":"2018-08-24T05:39:05Z","closed_at":null,"author_association":"NONE","body":"I have an audio file with sampling frequency = 48K. The length of the audio file is 258 second, which means 12384000 samples.  the number features vectors I got using your algorithm is 2559. What I'm looking for is, for instance, what are the corresponding times related to the first feature vector? "},"comment":{"url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/comments/415656632","html_url":"https://github.com/ganesa90/speech-inversion-dnn/issues/2#issuecomment-415656632","issue_url":"https://api.github.com/repos/ganesa90/speech-inversion-dnn/issues/2","id":415656632,"node_id":"MDEyOklzc3VlQ29tbWVudDQxNTY1NjYzMg==","user":{"login":"ganesa90","id":11482671,"node_id":"MDQ6VXNlcjExNDgyNjcx","avatar_url":"https://avatars2.githubusercontent.com/u/11482671?v=4","gravatar_id":"","url":"https://api.github.com/users/ganesa90","html_url":"https://github.com/ganesa90","followers_url":"https://api.github.com/users/ganesa90/followers","following_url":"https://api.github.com/users/ganesa90/following{/other_user}","gists_url":"https://api.github.com/users/ganesa90/gists{/gist_id}","starred_url":"https://api.github.com/users/ganesa90/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/ganesa90/subscriptions","organizations_url":"https://api.github.com/users/ganesa90/orgs","repos_url":"https://api.github.com/users/ganesa90/repos","events_url":"https://api.github.com/users/ganesa90/events{/privacy}","received_events_url":"https://api.github.com/users/ganesa90/received_events","type":"User","site_admin":false},"created_at":"2018-08-24T05:39:05Z","updated_at":"2018-08-24T05:39:05Z","author_association":"OWNER","body":"The features extracted are the Tract Variables. They are sampled at 100Hz. So, for a 258 second audio, you will get nearly 2580 samples for the TVs. Each sample is 10ms apart."}}
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