Merge pull request #5703 from jctian98/master

fix a small issue in OWSM decode_long

espnet2/bin/s2t_inference.py

@@ -531,6 +531,7 @@ def decode_long(
         end_time_threshold: str = "<29.00>",
         lang_sym: Optional[str] = None,
         task_sym: Optional[str] = None,
+        skip_last_chunk_threshold: float = 0.2,
     ):
         """Decode unsegmented long-form speech.
 
@@ -566,17 +567,25 @@ def decode_long(
         if isinstance(speech, np.ndarray):
             speech = torch.tensor(speech)
 
-        assert (
-            speech.dim() == 1
-        ), f"speech must have one dimension, got size {speech.size()} instead"
+        if speech.dim() > 1:
+            assert (
+                speech.dim() == 2 and speech.size(1) == 1
+            ), f"speech of size {speech.size()} is not supported"
+            speech = speech.squeeze(1)  # (nsamples, 1) --> (nsamples,)
 
         utterances = []
         offset = 0
         text_prev = init_text
         while offset < len(speech):
             logging.info(f"Current start time in seconds: {offset / fs:.2f}")
-
             segment = speech[offset : offset + segment_len]
+            if len(segment) / fs < skip_last_chunk_threshold:
+                logging.warning(
+                    f"Skip the last chunk as it's too short: {len(segment) / fs:.2f}s"
+                )
+                offset += segment_len
+                continue
+
             # segment will be padded in __call__
             result = self.__call__(
                 speech=segment,
@@ -641,7 +650,6 @@ def decode_long(
                 utterances.append(utt)
 
             offset += round((new_start_time_id - first_time_id) * resolution * fs)
-            self.time_id = first_time_id
 
         return utterances