The authors built FOACoder, a spatial encoder that processes First Order Ambisonics, a four-channel representation encoding sound pressure and direction.
Spatial audio model localizes and transcribes sounds across smart-glasses arrays
SEA-LM combines spatial and mono audio encoders to identify, locate and transcribe overlapping sounds while distinguishing the wearer from nearby speakers.
Big Tech
Sonal Kumar · Sinan Hersek · Artem Dementyev · Mengzhen Pan · Ishan Chatterjee · Anurag Kumar · +3 more
University of Maryland, College Park · Google · Google DeepMind
Research Digest··2 min read
Kumar and colleagues developed SEA-LM, an audio-language model designed for egocentric, multichannel recordings from smart glasses.
Why this paper
From Google and 2 others
In one line
SEA-LM enables spatial audio understanding from wearable microphone arrays, outperforming baselines in localization and transcription.
What we could check
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- ✓Limitations stated by the authors (3 noted)
- ✓Reports numbers on named benchmarks
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