Fix/speecht5 bug
Author: NimaYaqmuri
Pull request: yes

# What does this PR do?

Fixes a Critical Issue in SpeechT5 Speech Decoder Prenet and Enhances Test Suite

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
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- [x] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

@ylacombe
@sanchit-gandhi
@Spycsh


Key Changes:
------------
*   **Critical Bug Fix in Speech Decoder Prenet**: I discovered that the `repeat` operation in the speech decoder prenet's forward method was mistakenly duplicating the `speaker_embeddings` tensor. This erroneous behavior, likely an oversight in previous contributions, resulted in incorrect tensor dimensions for concatenation, leading to raised errors and halting the training process
    
*   **Refined Testing Approach**: Alongside this fix, I have updated the SpeechT5ForTextToSpeechIntegrationTests. These updates include:
  
    *   **Adaptability to Variability in Sequence Lengths**: Modifications to handle variability due to dropout in the speech decoder pre-net, ensuring test reliability against random variations.
    *   **Dynamic Dimension Checks**: Replacement of hardcoded dimensions with dynamic checks based on the model's configuration and seed settings, ensuring test validity across various scenarios.
    *   **New and Improved Test Cases**: Introduction of new test cases for validation of spectrogram and waveform shapes, addressing potential issues in speech generation and vocoder processing.
    *   **Correction of Misassumptions in Tests**: Adjustment of existing test cases where previous assumptions about output shapes led to inaccuracies. This includes considering varying batch sizes in tests, which were not adequately addressed before, possibly due to an oversight in considering the speaker embeddings' shape (initially 1x512) in batch scenarios.

Comments:
To observe the issue addressed by this PR, visit the [Hugging Face SpeechT5 Fine-Tuning Tutorial](https://huggingface.co/learn/audio-course/chapter6/fine-tuning). During training, you encounter a concatenation error due to incorrect dimensions.

Thanks for your advice! I'm going to tweak the `generate_speech` for these two cases.

Hello @ylacombe , @sanchit-gandhi and @ArthurZucker

I've implemented your suggestions and made updates to the SpeechT5 Text to Speech class. My focus was on improving how we handle speaker embeddings in two key scenarios:

1.  **Matching Batch Size**: When there's one embedding per sample.
2.  **One-to-Many**: When a single embedding is used for all samples in the batch.

Key updates include:
--------------------

*   **Embedding Replication**: Introduced logic to replicate a single speaker embedding across multiple samples when necessary.
*   **Error Handling**: Implemented a ValueError to alert for dimension mismatches in speaker embeddings.
*   **Testing**: Added comprehensive test cases to ensure robust functionality across both scenarios.

Additionally, I've adapted the handling of speaker embedding dimensions outside the main model classes, aligning with the approach used in the original [SpeechT5 implementation by Microsoft](https://github.com/microsoft/SpeechT5). This decision avoids altering the SpeechT5 speech decoder's pre-net forward method, maintaining consistency with the existing model structure.

Please let me know if there are other scenarios or considerations I should account for. Your feedback is greatly appreciated.

Thank you for your guidance,

Nima Yaqmuri

It seems there exists a related issue, [Issue #28189](https://github.com/huggingface/transformers/issues/28189), which my PR's speaker embedding updates could potentially address.

Alongside the issue highlighted by @ylacombe in the Hugging Face thread "[Audio Course Unit 6: Unable to Train SpeechT5](https://discuss.huggingface.co/t/audio-course-unit-6-unable-to-train-speech-t5/68888)", my PR also aims to resolve a similar problem outlined in "[SpeechT5 Text-to-Speech Fine-Tuning Runtime Error](https://discuss.huggingface.co/t/speecht5-text-to-speech-fine-tuning-runtime-error/67472)", which seems to be related to the solution.

Hi @ylacombe and @amyeroberts,

Thanks a lot for your valuable feedback and approvals!

I've implemented the suggested changes, introducing randomized speaker embeddings with a fixed seed in the `speecht5` tests. 

Additionally, I've run all the relevant slow tests for `speecht5` on my end, and everything works as expected. It seems we're ready for the merge.

I appreciate your support and guidance throughout this process!

Best.

Thanks again @NimaYaqmuri for this great contribution!