Fix more typos.

egs/librispeech/ASR/transducer_stateless/alignment.py

@@ -135,7 +135,7 @@ def force_alignment(
 
     Caution:
       We assume that the maximum number of sybmols per frame is 1.
-      That is, the model should be training using a nonzero value
+      That is, the model should be trained using a nonzero value
       for the option `--modified-transducer-prob` in train.py.
 
     Args:
@@ -163,6 +163,7 @@ def force_alignment(
 
     T = encoder_out.size(1)
     U = len(ys)
+    assert 0 < U <= T
 
     encoder_out_len = torch.tensor([1])
     decoder_out_len = encoder_out_len
@@ -204,7 +205,7 @@ def force_alignment(
 
         for i, item in enumerate(A):
             if (T - 1 - t) >= (U - item.pos_u):
-                # horizontal transition
+                # horizontal transition (left -> right)
                 new_item = AlignItem(
                     log_prob=item.log_prob + log_probs[i][blank_id],
                     ys=item.ys + [blank_id],
@@ -213,7 +214,7 @@ def force_alignment(
                 B.append(new_item)
 
             if item.pos_u < U:
-                # diagonal transition
+                # diagonal transition (lower left -> upper right)
                 u = ys[item.pos_u]
                 new_item = AlignItem(
                     log_prob=item.log_prob + log_probs[i][u],
@@ -221,13 +222,14 @@ def force_alignment(
                     pos_u=item.pos_u + 1,
                 )
                 B.append(new_item)
+
         if len(B) > beam_size:
             B = B.topk(beam_size)
 
     ans = B.topk(1)[0].ys
 
     assert len(ans) == T
-    assert list(filter(lambda i: i != 0, ans)) == ys
+    assert list(filter(lambda i: i != blank_id, ans)) == ys
 
     return ans
 
@@ -235,7 +237,7 @@ def force_alignment(
 def get_word_starting_frame(
     ali: List[int], sp: spm.SentencePieceProcessor
 ) -> List[int]:
-    """Get the starting frame of each word from the given alignments.
+    """Get the starting frame of each word from the given token alignments.
 
     When a word is encoded into BPE tokens, the first token starts
     with underscore "_", which can be used to identify the starting frame

egs/librispeech/ASR/transducer_stateless/compute_ali.py

@@ -85,7 +85,7 @@ def get_parser():
         type=str,
         required=True,
         help="""Output directory.
-        It contains 3 generated files:
+        It contains 2 generated files:
 
         - token_ali_xxx.h5
         - cuts_xxx.json.gz
@@ -322,8 +322,5 @@ def main():
     done_file.touch()
 
 
-#  torch.set_num_threads(1)
-#  torch.set_num_interop_threads(1)
-
 if __name__ == "__main__":
     main()