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| | rowspan="8"|2017.12.25 | | | rowspan="8"|2017.12.25 |
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| + | |Miao Zhang |
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Date |
People |
Last Week |
This Week |
Task Tracking
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2017.12.25
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Miao Zhang
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Ying Shi
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- some function for voice-printer
- speaker vector per utterance here
- speaker vector minus base speaker vector here
- CTC for Haibo Wang (Token accuracy on train set 92.80%, on cv set 89.74%) haven't test on test set
- QRcode
- speaker vector merge phone grayscale here
- speaker vector merge phone black-and-white map here
- speaker vector merge phone black-and-white map minus base vector here
- ivector baseline for kazak-uyghur LRE performance is 81.85% (Utt level)
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- Finish voice-checker copyright and submit the copyright in this Wednesday
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Lantian Li
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- Complete the recipe for `VV_FACTOR`.
- 16K and 8K deep speaker model comparison.[1]
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- Patent for `VV_QuickMark`.
- Complete the demo for `VV_FACTOR`.[Assign to Shouyi Dai]
- Phonetic speaker embedding.
- Overlap training for speaker features.
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Zhiyuan Tang
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- word level pronunciation accuracy based on likelihood (tell which word is well pronounced as '0' or badly pronounced '1')
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- model adaptation
- if possible, an alpha version Parrot for test inside lab to collect some data for better configurature
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Date |
People |
Last Week |
This Week |
Task Tracking
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2017.12.18
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Ying Shi
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- Finish the Voice-printer program
- Apply the software copyright of Voice-printer
- APSIPA 2017
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- Finish the software copyright of Voice-checker
- Baseline of similar language recongnition system(i-vector, DNN, PTN)
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- focus on function other than UI
- i-vector LID first
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Lantian Li
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- Optimize the demo of `VV_Seg` and `VV_QuickMark`.
- Phone-aware scorning on deep speaker feature. [2]
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- Phone-aware scorning.
- Overlap training for speaker features.
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Zhiyuan Tang
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- easy-to-read interfaces for Parrot
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- phone-level likelihood for detail diagnosis and an alpha version Parrot for test inside lab
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