Comments (1)
mimbres
commented on May 30, 2024
@kasireddygariDineshKumarReddy
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As you know, the goal of fingerprinting is to identify the source audio file, not the sound generating source. The same dogs' barking every time will differ in audio signal, and of course, they can't be positive pair in this project. In fact, your scenario is the same as standard sound event detection.
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Perhaps your question is about the figure 2 in our paper. Any sample in the training batch has a chance to be anchored once. For example, the red original circle is an anchor to be compared with others in the first row. You may find the red circle in the second rows but the anchor in the row is pink circle. We compute softmax crossentropy on each row.
from neural-audio-fp.
Related Issues (20)
- Unable to open the file "../demo_template.ipynb" HOT 1
- Speed of generating fingereprints from custom source HOT 8
- Questions about inquiries HOT 8
- Could you please provide the checksum of fma_full only? HOT 8
- Why the loss computed during training is NanοΌ HOT 9
- permission denied for building Docker Custom Image HOT 5
- FileNotFoundError: [Errno 2] No such file or directory: './logs/emb/CHECKPOINT_NAME/CHECKPOINT_INDEX/query_shape.npy' HOT 4
- IS THIS REPOSITORY HELPFUL FOR FOLLOWING SITUATION HOT 1
- Dimension of Zt HOT 7
- Getting training loss value as nan and val loss as nan HOT 8
- question: my modle train loss:nan HOT 2
- Comparing short audio files HOT 1
- finetuning on short audios HOT 5
- Evaluation with custom dataset HOT 7
- Fingerprint generation from custom dataset HOT 2
- Reported train, val, test split sizes vs actual FMA size HOT 3
- Questions Regarding Custom Data Testing in Audio Fragment Identification HOT 1
- Model Definition Front Strides HOT 1
- UnboundLocalError in run.py during training HOT 3
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from neural-audio-fp.