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+and+automatic+speech+translation+(AST).+However%252C+these+methods+often+overlook+the+critical+aspect+of+language+adaptation+in+multilingual+settings%252C+relying+instead+on+multilingual+data+without+adequately+addressing+language+differences.+To+address+this+gap%252C+we+propose+the+Ideal-LLM+model%252C+which+employs+dual+multilingual+encoders+to+enrich+language+feature+information+and+utilizes+a+language-adapted+connector+to+target+the+adaptation+of+each+language+specifically.+By+leveraging+the+complementary+strengths+of+Whisper+and+MMS+encoders%252C+our+approach+ensures+richer+multilingual+representations.+Additionally%252C+the+language-adapted+connector+enhances+modal+transformation+via+a+language+weight+selector+tailored+for+each+language.+Experimental+results+demonstrate+that+Ideal-LLM+significantly+improves+ASR+performance%252C+achieving+a+32.6%2525+relative+reduction+in+average+word+error+rates+compared+to+the+standard+speech+encoder+integrated+with+LLMs+and+yields+an+average+BLEU+score+of+36.78+for+AST+task.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.0e5fab4be699766fb5e6adb6eebb0489%3frik%3dxdggMkYSj26oWg%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=LLM+and+Chatgpt+Diagram&FORM=IRPRST&ck=3BFB85BE41157C6A28182F2981DB8129&selectedIndex=3&itb=0)
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