Papers › Lightweight Transducer Based on Frame-Level Criterion
Lightweight Transducer Based on Frame-Level Criterion
Genshun Wan, Mengzhi Wang, Tingzhi Mao, Hang Chen, Zhongfu Ye
The transducer model trained based on sequence-level criterion requires a lot of memory due to the generation of the large probability matrix. We proposed a lightweight transducer model based on frame-level criterion, which uses the results of the CTC forced alignment algorithm to determine the label for each frame. Then the encoder output can be combined with the decoder output at the corresponding time, rather than adding each element output by the encoder to each element output by the decoder as in the transducer. This significantly reduces memory and computation requirements. To address the problem of imbalanced classification caused by excessive blanks in the label, we decouple the blank and non-blank probabilities and truncate the gradient of the blank classifier to the main network. Experiments on the AISHELL-1 demonstrate that this enables the lightweight transducer to achieve similar results to transducer. Additionally, we use richer information to predict the probability of blank, achieving superior results to transducer.
Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speech Recognition | AISHELL-1 | Lightweight Transducer With LM | Params(M) | 45.3 | #7 of 18 | Archive leaderboard | report |
| Speech Recognition | AISHELL-1 | Lightweight Transducer With LM | Word Error Rate (WER) | 4.03 | #7 of 18 | Archive leaderboard | report |
| Speech Recognition | AISHELL-1 | Lightweight Transducer | Params(M) | 45.3 | #10 of 18 | Archive leaderboard | report |
| Speech Recognition | AISHELL-1 | Lightweight Transducer | Word Error Rate (WER) | 4.31 | #10 of 18 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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