Cutting off invalid frames of encoder_embed output

egs/librispeech/ASR/pruned_transducer_stateless/decode_stream.py

@@ -115,6 +115,7 @@ class DecodeStream(object):
         ]
         self.num_processed_frames += (
             chunk_size
+            - 2 * self.params.subsampling_factor
             - self.params.right_context * self.params.subsampling_factor
         )
 

egs/librispeech/ASR/pruned_transducer_stateless2/conformer.py

@@ -272,6 +272,9 @@ class Conformer(EncoderInterface):
              given {states[1].shape}."""
 
             # src_key_padding_mask = make_pad_mask(lengths + left_context)
+
+            lengths -= 2  # we will cut off 1 frame on each side of encoder_embed output
+
             src_key_padding_mask = make_pad_mask(lengths)
 
             assert processed_lens is not None
@@ -287,6 +290,9 @@ class Conformer(EncoderInterface):
             )
 
             embed = self.encoder_embed(x)
+
+            embed = embed[:, 1:-1, :]
+
             embed, pos_enc = self.encoder_pos(embed, left_context)
             embed = embed.permute(1, 0, 2)  # (B, T, F) -> (T, B, F)
 

egs/librispeech/ASR/pruned_transducer_stateless2/streaming_decode.py

@@ -357,7 +357,7 @@ def decode_one_chunk(
 
     for stream in decode_streams:
         feat, feat_len = stream.get_feature_frames(
-            params.decode_chunk_size * params.subsampling_factor
+            (params.decode_chunk_size + 2) * params.subsampling_factor
         )
         features.append(feat)
         feature_lens.append(feat_len)
@@ -371,7 +371,7 @@ def decode_one_chunk(
 
     # if T is less than 7 there will be an error in time reduction layer,
     # because we subsample features with ((x_len - 1) // 2 - 1) // 2
-    tail_length = 7 + params.right_context * params.subsampling_factor
+    tail_length = 15 + params.right_context * params.subsampling_factor
     if features.size(1) < tail_length:
         feature_lens += tail_length - features.size(1)
         features = torch.cat(