Update hyperparams.yaml

hyperparams.yaml

@@ -122,11 +122,6 @@ transducer_lin: !new:speechbrain.nnet.linear.Linear
    n_neurons: !ref <output_neurons>
    bias: False
 
-log_softmax: !new:speechbrain.nnet.activations.Softmax
-   apply_log: True
-
-# for MTL
-# update model if any HEAD module is added
 modules:
    CNN: !ref <CNN>
    enc: !ref <enc>
@@ -138,10 +133,7 @@ modules:
    proj_ctc: !ref <proj_ctc>
    proj_dec: !ref <proj_dec>
    proj_enc: !ref <proj_enc>
-#   dec_lin: !ref <dec_lin>
 
-# for MTL
-# update model if any HEAD module is added
 model: !new:torch.nn.ModuleList
    - [!ref <CNN>, !ref <enc>, !ref <emb>, !ref <dec>, !ref <proj_enc>, !ref <proj_dec>, !ref <proj_ctc>, !ref <transducer_lin>]
 
@@ -163,7 +155,6 @@ Beamsearcher: !new:speechbrain.decoders.transducer.TransducerBeamSearcher
    blank_id: !ref <blank_index>
    beam_size: !ref <beam_size>
    nbest: !ref <nbest>
-   # FIXME: when lm pretrained, use this
    # lm_module: !ref <lm_model>
    # lm_weight: !ref <lm_weight>
    state_beam: !ref <state_beam>
@@ -186,7 +177,9 @@ fea_streaming_extractor: !new:speechbrain.lobes.features.StreamingFeatureWrapper
       - !ref <compute_features>
       - !ref <normalize>
       - !ref <CNN>
-   # don't consider normalization as part of the input filter chain
+   # don't consider normalization as part of the input filter chain.
+   # normalization will operate at chunk level, which mismatches training
+   # somewhat, but does not appear to result in noticeable degradation.
    properties: !!python/object/apply:speechbrain.utils.filter_analysis.stack_filter_properties
       - [!ref <compute_features>, !ref <CNN>]