AI models
MLN-ASR
Training compute
3×10⁸ FLOP
Parameters
10K
Published
Aug 1, 1988
MLN-ASR is an AI model developed by McGill University (Canada), first published in August 1988. It works in the speech domain, on tasks such as speech recognition (asr).
Training it took an estimated 3×10⁸ FLOP of compute (estimation method: hardware). The model has 10,000 parameters. It was trained on roughly 12.6K datapoints.
Epoch AI rates the confidence of this record as confident.
Full record
- Organization
- McGill University
- Country of organization
- Canada
- Domain
- Speech
- Task
- Speech recognition (ASR)
- Training compute
- 3×10⁸ FLOP
- Compute estimation method
- Hardware
- Parameters
- 10,000
- Dataset size
- 12.6K
- Training time
- 0 h
- Epoch confidence
- Confident
SourceEpoch AI, 'AI Models'. Published online at epoch.ai. Retrieved 2026-07-29 from https://epoch.ai/data/ai-models. Licensed under CC BY 4.0.
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