add contribution section

CONTRIBUTING.md

-
-# TODOs
-add possibility to train without description column
-        # TODO: add CE per codebook
\ No newline at end of file

README.md

@@ -15,7 +15,7 @@ by Dan Lyth and Simon King, from Stability AI and Edinburgh University respectiv
 
 Contrarily to standard TTS models, Parler-TTS allows you to directly describe the speaker characteristics with a simple text description where you can modulate gender, pitch, speaking style, accent, etc.
 
-## Inference
+## Usage
 
 > [!TIP]
 > You can directly try it out in an interactive demo [here](TODO: add link to spaces)!
@@ -44,7 +44,6 @@ sf.write("parler_tts_out.wav", audio_arr, model.config.sampling_rate)
 ```
 
 
-
 ## Installation steps
 
 Parler-TTS has light-weight dependencies and can be installed in one line:
@@ -75,6 +74,24 @@ Special thanks to:
 - Dan Lyth and Simon King, from Stability AI and Edinburgh University respectively, for publishing such a promising and clear research paper: [Natural language guidance of high-fidelity text-to-speech with synthetic annotations](https://arxiv.org/abs/2402.01912).
 - and the many libraries used, namely [datasets](https://huggingface.co/docs/datasets/v2.17.0/en/index), [accelerate](https://huggingface.co/docs/accelerate/en/index), [jiwer](https://github.com/jitsi/jiwer), [wandb](https://wandb.ai/), and [transformers](https://huggingface.co/docs/transformers/index).
 
+## Contribution
+
+Contributions are welcome, as the project offers many possibilities for improvement and exploration.
+
+Namely, we're looking at ways to improve both quality and speed:
+- Datasets:
+    - Train on more data
+    - Add more features such as accents
+- Training:
+    - Add PEFT compatibility to do Lora fine-tuning.
+    - Add possibility to train without description column.
+    - Explore multilingual training.
+    - Explore mono-speaker finetuning.
+    - Explore more architectures.
+- Optimization:
+    - Compilation and static cache
+    - Support to FA2 and SDPA
+
 ## Citation
 ```
 @misc{lacombe-etal-2024-parler-tts,