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--- |
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license: apache-2.0 |
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pipeline_tag: audio-text-to-text |
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--- |
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# OLMoASR |
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OLMoASR is a series of English automatic speech recognition (ASR) models proposed in the [OLMoASR: Open Models and Data for Training Robust Speech Recognition Models](https://github.com/allenai/OLMoASR.git) |
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paper by Huong Ngo et al. from Ai2. Trained on 440K hours of weakly-supervised audio-text pairs collected from the public internet, OLMoASR demonstrates strong robustness and zero-shot capabilities. Visit the |
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[OLMoASR repository](https://github.com/allenai/OLMoASR.git) for access to data processing, training and evaluation code. |
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# Model Details |
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OLMoASR uses a Transformer-based encoder-decoder architecture and is an audio language model (LM), where there is an audio encoder and language decoder. |
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OLMoASR has 5 different model sizes and all checkpoints are trained with English-only data. Below is a table enumerating the different model sizes and associated parameter count. |
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| Size | Parameters | |
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|-----------|------------| |
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| tiny | 39 M | |
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| base | 74 M | |
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| small | 244 M | |
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| medium | 769 M | |
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| large | 1.5 B | |
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| large-v2 | 1.5 B | |
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# Training Data |
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OLMoASR is trained on 440K hours of weakly-supervised data subsampled from OLMoASR-Mix, a filtered version of [OLMoASR-Pool](link). |
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OLMoASR-Mix is a collection 1M hours of audio-text pairs, curated from the 3M hours of OLMoASR-Pool. |
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# Usage |
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To perform transcription, you can run |
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``` |
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import olmoasr |
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model = olmoasr.load_model("medium", inference=True) |
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result = model.transcribe("audio.mp3") |
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print(result) |
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``` |
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# Evaluation |
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To perform evaluation, you can visit the [OLMoASR repository](https://github.com/allenai/OLMoASR.git) for more details. |
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# License |
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This model is licensed under Apache 2.0. It is intended for research and educational use in accordance with [Ai2's Responsible Use Guidelines](https://allenai.org/responsible-use). |
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# BibTeX entry and citation info |
