Venue: ICLR 2023 TinyPapers

Reviews:

final_score: rating: Great Start (GS): a submission which meets some of the reviewing criteria but has room for improvement
review_content: summary_of_contributions: In this article, author(s) tried to explain the pipeline for input (video, text) data conversion approach to improve emotion recognition performance on the MELD dataset. 
strengths_and_weaknesses: ## Strengths: 
- The brief introduction is easy and quick to understand. 
- The selection of dataset "MELD" is related to the article's focus.
- Related work is fairly explained

## Weakness
- The title of article don't match with the content of article. 
- The author's missed to convenience the experiment implementation.
- The article shows contradictory results in the table and conclusion section.
-  The figure demonstrated in the article don't show significant explanation of the implementation
- Implementaion reference is completely missing.  
suggested_changes: - Correct the tittle of the article
- Correct the experiment results, as different value of the score in mentioned. 
- Add reference to see if the mentioned results is ground truth or just an assumption. 
- Some related recent SOTA references are missing, Please try to include references. 
- As a reader, I am inconvenienced with the results. Try to mention it with source code or some demonstration link reference. 
- If no source code is available, try to exclude score value achieved in your model. It's fair enough to propose this idea without any results.
review_title: null

final_score: rating: Needs Clarification (NC): a submission which does not meet the reviewing criteria and needs clarification for its described problem or solution
review_content: summary_of_contributions: Authors explore the effect of modality conversion (audio to text) on sentiment analysis. The approach seems promising, but more clarification and investigation are necessary. 
strengths_and_weaknesses: Strengths
1) Innovative idea, and potential for impact.

Weaknesses: 
1) There are several typos in the paper
2) More investigations/examples are necessary to ascertain that the modality conversion is actually working. The authors just use one example in the paper.
suggested_changes: 1) The title is erroneous.
2) There are several minor typos in the paper
3) The WF1 is reported three times in the paper and each of them has a different value. This definitely needs clarification/explanation. 
3) It would be good to have at least one or two more examples like Figure 1
4) Table caption is erroneous
review_title: null

Decision: Invite to revise