Question/Issue:
[Describe the question or issue in detail]
Hello,
I’m wondering if it is possible to use the AI labeling block “Edge Impulse Inc / Audio labeling with AudioSet” to automatically take in a 5 minute recording that contains multiple instances of a 2s audio recording apply labels either to each instance of audio, or split up the recording into multiple files, 1 for each 2s recording.
I’m currently doing it manually and am trying to figure out how to leverage this tool to speed that up. The labels I have are custom and it seems to be reporting an error if I don’t use one of the predefined ones on the list.
My model is already partially trained on these keywords and recognizing them fairly accurately so I’m wondering if I can leverage that to build out the rest of the training and sample data faster than doing it all manually?
Currently I take in a 30s recording filled with as many instances of the audio as I can get in that window and then I go in and use the “split” feature to turn it into multiple files by manually setting bounding boxes over the audio after I listen to it verify the beginning and end of the key words.
Project ID:
[Provide the project ID]
663220
Context/Use case:
[Provide context or use case where the issue is encountered]
Steps Taken:
- In Data acquisition go to AI labeling
- Select Audio labeling with AudioSet
- Connect HuggingFace API Key
- Enter customer labels of interest
Expected Outcome:
[Describe what you expected to happen]
I was hoping if the model is trained up enough it can recognize the custom keywords and I can help it automate the rest of the process to save me time.
Actual Outcome:
[Describe what actually happened]
Job fails
Reproducibility:
- [ *] Always
- [ ] Sometimes
- [ ] Rarely
Environment:
- Platform: [Arduino Nano 33 BLE Sense]
- Build Environment Details: [e.g., Arduino IDE 1.8.19 ESP32 Core for Arduino 2.0.4]
- OS Version: [e.g., Ubuntu 20.04, Windows 10]
- Edge Impulse Version (Firmware): [Website but v1.32.0]
- To find out Edge Impulse Version:
- if you have pre-compiled firmware: run edge-impulse-run-impulse --raw and type AT+INFO. Look for Edge Impulse version in the output.
- if you have a library deployment: inside the unarchived deployment, open model-parameters/model_metadata.h and look for EI_STUDIO_VERSION_MAJOR, EI_STUDIO_VERSION_MINOR, EI_STUDIO_VERSION_PATCH
- Edge Impulse CLI Version: [e.g., 1.5.0]
- Project Version: [e.g., 1.0.0]
-
Custom Blocks / Impulse Configuration: [Time series data, Audio (MFCC), Classification (basically the keyword spotting example)]
Logs/Attachments:
[Include any logs or screenshots that may help in diagnosing the issue]
Additional Information:
[Any other information that might be relevant]