How to solve problem of a failed speech model

Question

I'm building a speech model on Azure. The data for training was successfully uploaded, but the model that uses the data failed with an "Internal error" message. Pls tell me what to do. Thanks!

Elise

Answer 1

Hello Elise,

Thank you for posting your question in the Microsoft Q&A forum.

When building a speech model on Azure and encountering an "Internal error" message, the issue could stem from various factors, such as data issues, service limitations, or configuration problems. However, you have not provided adequate information to understand few configurations on your end.

I am trying to provide you some steps to validate your current configurations; by following below steps you should be able to identify and resolve the cause of the "Internal error" and successfully train your speech model on Azure.

Below are the Steps:

Verify the data format, size, and quality.

Review the training configuration and parameters.

Check service quotas and resource limits.

Inspect logs and error details for more information.

Retry the training job or test with a smaller dataset.

Validate the data upload process and permissions.

Contact Azure Support if the issue persists.

Use Azure diagnostics tools to identify the root cause.

Test with a sample dataset to isolate the issue.

Update SDKs and tools to the latest versions.

Below are some useful pointers you may need to check to explore more info and validate:

• Ensure your training data is in the correct format. Azure Speech Service typically requires audio files in specific formats (e.g., WAV, MP3) and associated transcriptions in a supported format (e.g., plain text, JSON). Some reference link may be helpful for you to explore more as below:
  • https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-custom-speech-test-and-train#audio-data
  • https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-custom-speech-test-and-train#transcription-data
• Verify that the data size is within the allowed limits. Large datasets may require splitting into smaller chunks.
• Check for corrupted or invalid files in your dataset. Even a single corrupted file can cause the training process to fail.
• Ensure you have selected the correct model type (e.g., acoustic model, language model, or pronunciation model) for your use case.
• Double-check the training parameters, such as the language, base model, and customization options.
  • https://learn.microsoft.com/en-us/azure/ai-services/speech-service/how-to-custom-speech-train-model?pivots=speech-studio
• Ensure you haven’t exceeded the quota limits for your Azure Speech Service subscription. For example, there may be limits on the number of concurrent training jobs or the size of datasets.
  • https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-services-quotas-and-limits

If above answer helped, please do not forget to "Accept Answer" as this may help other community members to refer the info if facing similar issue.