From 51ea14f910d76c5c1a581098d3808a78fdb9fcd1 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期二, 31 一月 2023 17:33:56 +0800
Subject: [PATCH] fix paraformer bug, when predicts no token, silence

---
 funasr/bin/asr_inference_paraformer.py           |    6 ++++--
 funasr/bin/asr_inference_uniasr.py               |    4 ++--
 funasr/bin/asr_inference.py                      |    4 ++--
 funasr/bin/asr_inference_paraformer_timestamp.py |    2 +-
 funasr/bin/asr_inference_paraformer_vad_punc.py  |    4 +++-
 5 files changed, 12 insertions(+), 8 deletions(-)

diff --git a/funasr/bin/asr_inference.py b/funasr/bin/asr_inference.py
index 985ff50..4c6d2a4 100644
--- a/funasr/bin/asr_inference.py
+++ b/funasr/bin/asr_inference.py
@@ -368,7 +368,7 @@
 #         except TooShortUttError as e:
 #             logging.warning(f"Utterance {keys} {e}")
 #             hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-#             results = [[" ", ["<space>"], [2], hyp]] * nbest
+#             results = [[" ", ["sil"], [2], hyp]] * nbest
 #
 #         # Only supporting batch_size==1
 #         key = keys[0]
@@ -575,7 +575,7 @@
             except TooShortUttError as e:
                 logging.warning(f"Utterance {keys} {e}")
                 hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-                results = [[" ", ["<space>"], [2], hyp]] * nbest
+                results = [[" ", ["sil"], [2], hyp]] * nbest
             
             # Only supporting batch_size==1
             key = keys[0]
diff --git a/funasr/bin/asr_inference_paraformer.py b/funasr/bin/asr_inference_paraformer.py
index 01237f7..cb140eb 100644
--- a/funasr/bin/asr_inference_paraformer.py
+++ b/funasr/bin/asr_inference_paraformer.py
@@ -227,6 +227,8 @@
         pre_acoustic_embeds, pre_token_length, alphas, pre_peak_index = predictor_outs[0], predictor_outs[1], \
                                                                         predictor_outs[2], predictor_outs[3]
         pre_token_length = pre_token_length.round().long()
+        if torch.max(pre_token_length) < 1:
+            return []
         decoder_outs = self.asr_model.cal_decoder_with_predictor(enc, enc_len, pre_acoustic_embeds, pre_token_length)
         decoder_out, ys_pad_lens = decoder_outs[0], decoder_outs[1]
 
@@ -394,7 +396,7 @@
 #         results = speech2text(**batch)
 #         if len(results) < 1:
 #             hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-#             results = [[" ", ["<space>"], [2], hyp, 10, 6]] * nbest
+#             results = [[" ", ["sil"], [2], hyp, 10, 6]] * nbest
 #         time_end = time.time()
 #         forward_time = time_end - time_beg
 #         lfr_factor = results[0][-1]
@@ -621,7 +623,7 @@
             results = speech2text(**batch)
             if len(results) < 1:
                 hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-                results = [[" ", ["<space>"], [2], hyp, 10, 6]] * nbest
+                results = [[" ", ["sil"], [2], hyp, 10, 6]] * nbest
             time_end = time.time()
             forward_time = time_end - time_beg
             lfr_factor = results[0][-1]
diff --git a/funasr/bin/asr_inference_paraformer_timestamp.py b/funasr/bin/asr_inference_paraformer_timestamp.py
index 9560cb0..7e2e414 100644
--- a/funasr/bin/asr_inference_paraformer_timestamp.py
+++ b/funasr/bin/asr_inference_paraformer_timestamp.py
@@ -410,7 +410,7 @@
         results = speech2text(**batch)
         if len(results) < 1:
             hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-            results = [[" ", ["<space>"], [2], hyp, 10, 6]] * nbest
+            results = [[" ", ["sil"], [2], hyp, 10, 6]] * nbest
         time_end = time.time()
         forward_time = time_end - time_beg
         lfr_factor = results[0][-1]
diff --git a/funasr/bin/asr_inference_paraformer_vad_punc.py b/funasr/bin/asr_inference_paraformer_vad_punc.py
index 7a539e4..619e6fd 100644
--- a/funasr/bin/asr_inference_paraformer_vad_punc.py
+++ b/funasr/bin/asr_inference_paraformer_vad_punc.py
@@ -235,6 +235,8 @@
 
         predictor_outs = self.asr_model.calc_predictor(enc, enc_len)
         pre_acoustic_embeds, pre_token_length, alphas, pre_peak_index = predictor_outs[0], predictor_outs[1], predictor_outs[2], predictor_outs[3]
+        if torch.max(pre_token_length) < 1:
+            return []
         pre_token_length = pre_token_length.round().long()
         decoder_outs = self.asr_model.cal_decoder_with_predictor(enc, enc_len, pre_acoustic_embeds, pre_token_length)
         decoder_out, ys_pad_lens = decoder_outs[0], decoder_outs[1]
@@ -602,7 +604,7 @@
                     results = speech2text(**batch)
                     if len(results) < 1:
                         hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-                        results = [[" ", ["<space>"], [2], 0, 1, 6]] * nbest
+                        results = [[" ", ["sil"], [2], 0, 1, 6]] * nbest
                     time_end = time.time()
                     forward_time = time_end - time_beg
                     lfr_factor = results[0][-1]
diff --git a/funasr/bin/asr_inference_uniasr.py b/funasr/bin/asr_inference_uniasr.py
index d386ff1..4ecb1cc 100644
--- a/funasr/bin/asr_inference_uniasr.py
+++ b/funasr/bin/asr_inference_uniasr.py
@@ -391,7 +391,7 @@
 #         except TooShortUttError as e:
 #             logging.warning(f"Utterance {keys} {e}")
 #             hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-#             results = [[" ", ["<space>"], [2], hyp]] * nbest
+#             results = [[" ", ["sil"], [2], hyp]] * nbest
 #
 #         # Only supporting batch_size==1
 #         key = keys[0]
@@ -616,7 +616,7 @@
             except TooShortUttError as e:
                 logging.warning(f"Utterance {keys} {e}")
                 hyp = Hypothesis(score=0.0, scores={}, states={}, yseq=[])
-                results = [[" ", ["<space>"], [2], hyp]] * nbest
+                results = [[" ", ["sil"], [2], hyp]] * nbest
     
             # Only supporting batch_size==1
             key = keys[0]

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