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+have+shown+promise+for+human-like+conversations%252C+they+are+primarily+pre-trained+on+text+data.+Incorporating+audio+or+video+improves+performance%252C+but+collecting+large-scale+multimodal+data+and+pre-training+multimodal+LLMs+is+challenging.+To+this+end%252C+we+propose+a+Fusion+Low+Rank+Adaptation+(FLoRA)+technique+that+efficiently+adapts+a+pre-trained+unimodal+LLM+to+consume+new%252C+previously+unseen+modalities+via+low+rank+adaptation.+For+device-directed+speech+detection%252C+using+FLoRA%252C+the+multimodal+LLM+achieves+22%2525+relative+reduction+in+equal+error+rate+(EER)+over+the+text-only+approach+and+attains+performance+parity+with+its+full+fine-tuning+(FFT)+counterpart+while+needing+to+tune+only+a+fraction+of+its+parameters.+Furthermore%252C+with+the+newly+introduced+adapter+dropout%252C+FLoRA+is+robust+to+missing+data%252C+improving+over+FFT+by+20%2525+lower+EER+and+56%2525+lower+false+accept+rate.+The+proposed+approach+scales+well+for+model+sizes+from+16M+to+3B+parameters.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.183ebb7444661ce01773168380d7de6f%3frik%3dQ4WtrLmDV4dsnQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Azure+Speech+Services+Multimodal+or+Large+Language+Model&simid=608036304978451890&FORM=IRPRST&ck=C6DCD6AE36175D2D4A17DD8EB7076148&selectedIndex=13&itb=0)
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