Papers › CRF-based Single-stage Acoustic Modeling with CTC Topology
CRF-based Single-stage Acoustic Modeling with CTC Topology
Hongyu Xiang, Zhijian Ou
In this paper, we develop conditional random field (CRF) based single-stage (SS) acoustic modeling with connectionist temporal classification (CTC) inspired state topology, which is called CTC-CRF for short. CTC-CRF is conceptually simple, which basically implements a CRF layer on top of features generated by the bottom neural network with the special state topology. Like SS-LF-MMI (lattice-free maximum-mutual-information), CTC-CRFs can be trained from scratch (flat-start), eliminating GMM-HMM pre-training and tree-building. Evaluation experiments are conducted on the WSJ, Switchboard and Librispeech datasets. In a head-to-head comparison, the CTC-CRF model using simple Bidirectional LSTMs consistently outperforms the strong SS-LF-MMI, across all the three benchmarking datasets and in both cases of mono-phones and mono-chars. Additionally, CTC-CRFs avoid some ad-hoc operation in SS-LF-MMI.
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 | LibriSpeech test-clean | CTC-CRF 4gram-LM | Word Error Rate (WER) | 4.09 | #52 of 64 | Archive leaderboard | report |
| Speech Recognition | LibriSpeech test-other | CTC-CRF 4gram-LM | Word Error Rate (WER) | 10.65 | #48 of 53 | Archive leaderboard | report |
| Speech Recognition | WSJ dev93 | Convolutional Speech Recognition | Word Error Rate (WER) | 6.23 | #3 of 4 | Archive leaderboard | report |
| Speech Recognition | WSJ eval92 | CTC-CRF 4gram-LM | Word Error Rate (WER) | 3.79 | #15 of 17 | Archive leaderboard | report |
| Speech Recognition | WSJ eval93 | CTC-CRF 4gram-LM | Word Error Rate (WER) | 6.23 | #2 of 3 | 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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