readme: ---
  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.
  