1 INTRODUCTION

2 PRELIMINARIES

3 FEATURES AND CATEGORIZATION OF SR APPROACHES

4 SEQUENTIAL AND GRAPH NEURAL NETWORKS FOR SR

5 DATASETS, EVALUATION METRICS AND COMPLEXITY

6 CHALLENGES AND DIRECTIONS

7 CONCLUSION