| datasets: | |
| - AMI | |
| language: | |
| - en | |
| license: apache-2.0 | |
| metrics: | |
| - | |
| name: "IHM test WER" | |
| type: wer | |
| value: 17.40 | |
| - | |
| name: "SDM test WER" | |
| type: wer | |
| value: 32.21 | |
| - | |
| name: "GSS test WER" | |
| type: wer | |
| value: 22.43 | |
| tags: | |
| - k2 | |
| - icefall | |
| # AMI | |
| This is an ASR recipe for the AMI corpus. AMI provides recordings from the speaker's | |
| headset and lapel microphones, and also 2 array microphones containing 8 channels each. | |
| We pool data in the following 4 ways and train a single model on the pooled data: | |
| (i) individual headset microphone (IHM) | |
| (ii) IHM with simulated reverb | |
| (iii) Single distant microphone (SDM) | |
| (iv) GSS-enhanced array microphones | |
| Speed perturbation and MUSAN noise augmentation are additionally performed on the pooled | |
| data. | |
| ## Performance Record | |
| ### pruned_transducer_stateless7 | |
| The following are decoded using `modified_beam_search`: | |
| | Evaluation set | dev WER | test WER | | |
| |--------------------------|------------|---------| | |
| | IHM | 18.92 | 17.40 | | |
| | SDM | 31.25 | 32.21 | | |
| | MDM (GSS-enhanced) | 21.67 | 22.43 | | |
| See the [recipe](https://github.com/k2-fsa/icefall/tree/master/egs) for details. | |