Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection Article Swipe
Shruti Palaskar
,
Oggi Rudovic
,
Sameer Dharur
,
Florian Pesce
,
Gautam Krishna
,
Aswin Sivaraman
,
Jack Berkowitz
,
Ahmed Hussen Abdelaziz
,
Saurabh Adya
,
Ahmed H. Tewfik
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.09617
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2406.09617
Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-training multimodal LLMs is challenging. To this end, we propose a Fusion Low Rank Adaptation (FLoRA) technique that efficiently adapts a pre-trained unimodal LLM to consume new, previously unseen modalities via low rank adaptation. For device-directed speech detection, using FLoRA, the multimodal LLM achieves 22% 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, with the newly introduced adapter dropout, FLoRA is robust to missing data, improving over FFT by 20% lower EER and 56% lower false accept rate. The proposed approach scales well for model sizes from 16M to 3B parameters.
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- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2406.09617
- https://arxiv.org/pdf/2406.09617
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4399758722
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4399758722Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2406.09617Digital Object Identifier
- Title
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Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech DetectionWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-06-13Full publication date if available
- Authors
-
Shruti Palaskar, Oggi Rudovic, Sameer Dharur, Florian Pesce, Gautam Krishna, Aswin Sivaraman, Jack Berkowitz, Ahmed Hussen Abdelaziz, Saurabh Adya, Ahmed H. TewfikList of authors in order
- Landing page
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https://arxiv.org/abs/2406.09617Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2406.09617Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2406.09617Direct OA link when available
- Concepts
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Rank (graph theory), Adaptation (eye), Computer science, Fusion, Speech recognition, Voice activity detection, Natural language processing, Artificial intelligence, Speech processing, Psychology, Linguistics, Mathematics, Neuroscience, Philosophy, CombinatoricsTop concepts (fields/topics) attached by OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.approach | 85, 134 |
| abstract_inverted_index.dropout, | 112 |
| abstract_inverted_index.fraction | 102 |
| abstract_inverted_index.improves | 22 |
| abstract_inverted_index.proposed | 133 |
| abstract_inverted_index.relative | 75 |
| abstract_inverted_index.unimodal | 52 |
| abstract_inverted_index.improving | 119 |
| abstract_inverted_index.primarily | 13 |
| abstract_inverted_index.reduction | 76 |
| abstract_inverted_index.technique | 46 |
| abstract_inverted_index.text-only | 84 |
| abstract_inverted_index.Adaptation | 44 |
| abstract_inverted_index.collecting | 25 |
| abstract_inverted_index.detection, | 67 |
| abstract_inverted_index.human-like | 9 |
| abstract_inverted_index.introduced | 110 |
| abstract_inverted_index.modalities | 59 |
| abstract_inverted_index.multimodal | 27, 31, 71 |
| abstract_inverted_index.previously | 57 |
| abstract_inverted_index.adaptation. | 63 |
| abstract_inverted_index.counterpart | 95 |
| abstract_inverted_index.efficiently | 48 |
| abstract_inverted_index.fine-tuning | 93 |
| abstract_inverted_index.large-scale | 26 |
| abstract_inverted_index.parameters. | 105, 144 |
| abstract_inverted_index.performance | 88 |
| abstract_inverted_index.pre-trained | 14, 51 |
| abstract_inverted_index.Furthermore, | 106 |
| abstract_inverted_index.challenging. | 34 |
| abstract_inverted_index.performance, | 23 |
| abstract_inverted_index.pre-training | 30 |
| abstract_inverted_index.Incorporating | 18 |
| abstract_inverted_index.conversations, | 10 |
| abstract_inverted_index.device-directed | 65 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 10 |
| citation_normalized_percentile |