update the result of TED-EN-ZH

deepspeech/models/u2_st.py

@@ -113,7 +113,8 @@ class U2STBaseModel(nn.Layer):
                  asr_weight: float=0.0,
                  ignore_id: int=IGNORE_ID,
                  lsm_weight: float=0.0,
-                 length_normalized_loss: bool=False):
+                 length_normalized_loss: bool=False,
+                 **kwargs):
         assert 0.0 <= ctc_weight <= 1.0, ctc_weight
 
         super().__init__()
@@ -650,7 +651,7 @@ class U2STModel(U2STBaseModel):
                 odim=vocab_size,
                 enc_n_units=encoder.output_size(),
                 blank_id=0,
-                dropout_rate=model_conf['ctc_dropout_rate'],
+                dropout_rate=model_conf['ctc_dropoutrate'],
                 reduction=True,  # sum
                 batch_average=True,  # sum / batch_size
                 grad_norm_type=model_conf['ctc_grad_norm_type'])

examples/ted_en_zh/t0/README.md

@@ -6,5 +6,10 @@
 | Data Subset | Duration in Seconds |
 | --- | --- |
 | data/manifest.train | 0.942 ~ 60   |
-| data/manifest.dev   | 1.151 ~ 39   |  
+| data/manifest.dev   | 1.151 ~ 39   |
 | data/manifest.test  | 1.1 ~ 42.746 |
+
+## Transformer
+| Model | Params | Config | Char-BLEU |
+| --- | --- | --- | --- |
+| Transformer+ASR MTL | 50.26M | conf/transformer_joint_noam.yaml | 17.38 |

examples/ted_en_zh/t0/local/test.sh

@@ -19,7 +19,8 @@ for type in fullsentence; do
     --config ${config_path} \
     --result_file ${ckpt_prefix}.${type}.rsl \
     --checkpoint_path ${ckpt_prefix} \
-    --opts decoding.decoding_method ${type} decoding.batch_size ${batch_size}
+    --opts decoding.decoding_method ${type} \
+    --opts decoding.batch_size ${batch_size}
 
     if [ $? -ne 0 ]; then
         echo "Failed in evaluation!"