Understanding the Modality Gap: An Empirical Study on the Speech-Text Alignment Mechanism of Large Speech Language Models (2025.emnlp-main)
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| Challenge: | LSLMs have impressive conversational generation abilities, but consistently fall short of traditional pipeline systems on semantic understanding benchmarks. |
| Approach: | They propose to analyze the performance gap between speech and text inputs through a systematic experiment . they find that representation similarity is strongly correlated with the modality gap . |
| Outcome: | The proposed models improve the accuracy of speech inputs and their semantic understanding benchmarks. |
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