Top Tweets for #AudioML
Pretrained audio encoders encode spatial info unevenly. SARL benchmark reveals systematic biases in azimuth, elevation, distance, and room factors. Open-source evaluation framework released. #AudioML #SpatialAudio https://t.co/smNsn5nXkO
Universal audio encoder outperforms domain specialists via hybrid SSL and supervised distillation. Scales to 1B params. Drop-in for audio LLMs. #AudioML #AudioRepresentation https://t.co/ipLNQsvTG0
This isn't deepfake detection. It's codec artifact detection. Reads the encoder fingerprint, not the synthesis.
Mรผller et al. (2022): lab detectors under 1% EER hit 30%+ on real-world audio.
A perfect score isn't a model. It's a flag for what's leaking.
#AudioML
Imagine a noisy group call where 3 people talk at once.
This paper builds a model that can focus on a single speaker (using a short voice sample) and extract that voice.
This cleanup results in better, faster audio transcription.
Summary and full paper ๐
#AudioML #SpeechToText

๐Join us at the upcoming BISH Bash @ MathWorks!
๐
May 16 in Sunnyvale, CA/Virtual.
๐คTalks, networking, & bites!
Topics:
Spatial Audio Modeling ๐ง
Simulating a Clarinet ๐ท
Neural Network Tuning ๐ง
Music for Hearing Aids ๐
RSVP: https://t.co/j9MtHkB2CU
#AudioTech #AudioML
Has anyone experimented with #mixup in embedding space for audio-ML tasks? Curious about its effectiveness. Does it enhance model generalisation, improve performance? How would it compare to standard mixup? Would love to hear any experiences/insights! #AudioML #MachineLearning
Delivery day! Building my own microphone-amplifier circuits for experiments with #conditionmonitoring using audio.
#audioML #prototyping #machinelearning @Water_UofExeter

Latest work on learning audio features in a self-supervised setting with @neilzegh. Mel-scale initialized frontends perform worse than random initialization for SSL, and other differences!
#audioml #deeplearning
https://t.co/P1Pwak053p
With web app Demuxr, musicians can input an audio clip and isolate each instrument in order to create custom remixes they can practice with. ๐ต
@subramen and @jtannady break down how #opensource models PyTorch and Demucs make this happen: https://t.co/10aJhhdJs5

Congratulations to Anthony, Emma and team, doing pioneering work in the field of biodiversity and audio ML.
We are very proud of you Anthony!
#audioml #machinelearning #artificialintelligence #thefutureofdataishuman

Scan Band is a new #MachineLearning #AR tool that transforms objects around you into virtual instruments you can play with your body. An amazing collab with @Artiphon ๐๐ถ pushing @SnapAR #LensStudio to the maxxx ๐ช #ML #ScanBand #audioML
Try it here โ https://t.co/iblHCZuYGJ
Meet people at #AudioML, a new #Slack #community on #Audio & #MachineLearning. โซ + โ = โฅ :) https://t.co/8gjyFzEqD2

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