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# Task Name
Singing Voice Deepfake Detection
## Task Objective
Singing voice deepfake detection aims to identify AI-generated singing voice recordings. Its goal is to detect artificially gene…
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Currently you have provided the code for MoF evaluation.
Can you share the code you used for calculating other metrics reported in the paper?
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I noticed there are regularization args l1 and l2. But I cannot find the args about customizing loss function.
In evaluation,
```
%%ml evaluate regression
```
there are multiple metrics.
Wh…
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Is it possible to see the code used to compute the evaluation metrics as in the paper ("WhisperX: Time-Accurate Speech Transcription of Long-Form Audio")?
(as the devil's in the details...)
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### Main metrics:
- AUC
- AUC 0.1
- PPV
### Architecture
`evaluation.py`
```
def eval(y_actual, y_pred):
# ...
return AUC, AUC_01, PPV
```
### Notes
- Add shortcut to `impepd…
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This issue is a port from Alex's wish list for what it concerns the evaluation metrics
## Diagnostics / metrics - (measures of performance specific to neural data)
- [x] poisson_log_likelihood
- …
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- [x] Talk with Flavio and Malte about how using OSSC works
- [ ] Set up a master run_all file that we can give to Flavio and Malte so they can run our code on the supercomputer. This should run all…
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Hi,
I reproduced the paper on the HO3D data set according to the code you sent, but the result of F_aligned@5.0mm fluctuated between 52-54 and did not reach 56.4 in the paper. May I ask if you have c…
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# Task Name: Text-to-Music Generation
The Text-to-Music Generation task involves automatically creating music based on textual descriptions.
## Task Objective
This task aims to translate nar…
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Using your code of test.py and test dataset of FE240hz and VisEvent, I get your tracking results. Then I use the metrics evaluation code from the VisEvent project, [https://github.com/wangxiao5791509/…