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28 lines
1.3 KiB
Markdown
28 lines
1.3 KiB
Markdown
# 🧠 TopIPL: Iterative Pseudo-Labeling for ASR
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TopIPL is an **iterative pseudo-labeling algorithm** for training speech recognition models using both labeled and unlabeled data. It integrates seamlessly into the NeMo ASR pipeline and enables **self-training** across epochs with minimal manual intervention.
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## 🚀 Key Features
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- ⚙️ Supports **semi-supervised ASR training** with dynamic iterative pseudo-label refinement.
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- 🧪 Designed for large-scale training using both labeled and unlabeled speech data.
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- 🔁 Automatically writes pseudo-labels and updates training configs between iterations.
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## 📦 Required Components
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TopIPL relies on the following components:
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- **[`SDPNeMoRunIPLProcessor`]**
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Commands for running IPL are generated and submitted using SDP processors and NeMo-Run.
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See instructions for usage [here](https://github.com/NVIDIA/NeMo-speech-data-processor/blob/main/sdp/processors/ipl/README.md).
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- **Training Callback: `IPLEpochStopperCallback`**
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Add this to your training config under `exp_manager` to **stop training at the end of each epoch**, enabling pseudo-label update:
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```yaml
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exp_manager:
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create_ipl_epoch_stopper_callback: True
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ipl_epoch_stopper_callback_params:
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stop_every_n_epochs: n # Stop training after every n epochs (default: 1)
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