We are trying to use sentiment text to make the generated audio have different emotions
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- Dominant language
- Python
- Stars
- 15.3k
- Forks
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Description
Checks
- This template is only for feature request.
- I have thoroughly reviewed the project documentation but couldn't find any relevant information that meets my needs.
- I have searched for existing issues, including closed ones, and found not discussion yet.
- I confirm that I am using English to submit this report in order to facilitate communication.
1. Is this request related to a challenge you're experiencing? Tell us your story.
We are trying to use sentiment text to make the generated audio have different emotions
2. What is your suggested solution?
We are trying to use sentiment text to make the generated audio have different emotions
3. Additional context or comments
We tried to add emotional features for training. The data set was an English data set of about 330 hours and trained for 200k steps, but the effect of emotional guidance was not very good. If you are interested, we can discuss it together.
4. Can you help us with this feature?
- I am interested in contributing to this feature.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by reviewing the project's existing training and inference guidance for emotional conditioning, then define how sentiment text should affect generated audio and how results should be evaluated against the reported 330-hour, 200k-step training attempt.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100