From 3c3754dcc7568e76fa7d4b2c4e14849f68cc6ee7 Mon Sep 17 00:00:00 2001
From: 嘉渊 <wangjiaming.wjm@alibaba-inc.com>
Date: 星期日, 28 五月 2023 23:46:01 +0800
Subject: [PATCH] update repo

---
 funasr/bin/asr_infer.py |   40 ++++++++++++++++++++++++++++------------
 1 files changed, 28 insertions(+), 12 deletions(-)

diff --git a/funasr/bin/asr_infer.py b/funasr/bin/asr_infer.py
index 03145f8..9da7ef7 100644
--- a/funasr/bin/asr_infer.py
+++ b/funasr/bin/asr_infer.py
@@ -9,6 +9,7 @@
 import time
 import copy
 import os
+import re
 import codecs
 import tempfile
 import requests
@@ -488,15 +489,20 @@
 
                 nbest_hyps = nbest_hyps[: self.nbest]
             else:
-                yseq = am_scores.argmax(dim=-1)
-                score = am_scores.max(dim=-1)[0]
-                score = torch.sum(score, dim=-1)
-                # pad with mask tokens to ensure compatibility with sos/eos tokens
-                yseq = torch.tensor(
-                    [self.asr_model.sos] + yseq.tolist() + [self.asr_model.eos], device=yseq.device
-                )
+                if pre_token_length[i] == 0:
+                    yseq = torch.tensor(
+                        [self.asr_model.sos] + [self.asr_model.eos], device=yseq.device
+                    )
+                    score = torch.tensor(0.0, device=yseq.device)
+                else:
+                    yseq = am_scores.argmax(dim=-1)
+                    score = am_scores.max(dim=-1)[0]
+                    score = torch.sum(score, dim=-1)
+                    # pad with mask tokens to ensure compatibility with sos/eos tokens
+                    yseq = torch.tensor(
+                        [self.asr_model.sos] + yseq.tolist() + [self.asr_model.eos], device=yseq.device
+                    )
                 nbest_hyps = [Hypothesis(yseq=yseq, score=score)]
-
             for hyp in nbest_hyps:
                 assert isinstance(hyp, (Hypothesis)), type(hyp)
 
@@ -749,10 +755,13 @@
             feats = cache_en["feats"]
             feats_len = torch.tensor([feats.shape[1]])
             self.asr_model.frontend = None
+            self.frontend.cache_reset()
             results = self.infer(feats, feats_len, cache)
             return results
         else:
             if self.frontend is not None:
+                if cache_en["start_idx"] == 0:
+                    self.frontend.cache_reset()
                 feats, feats_len = self.frontend.forward(speech, speech_lengths, cache_en["is_final"])
                 feats = to_device(feats, device=self.device)
                 feats_len = feats_len.int()
@@ -820,9 +829,16 @@
 
                 # Change integer-ids to tokens
                 token = self.converter.ids2tokens(token_int)
-                token = " ".join(token)
-
-                results.append(token)
+                postprocessed_result = ""
+                for item in token:
+                    if item.endswith('@@'):
+                        postprocessed_result += item[:-2]
+                    elif re.match('^[a-zA-Z]+$', item):
+                        postprocessed_result += item + " "
+                    else:
+                        postprocessed_result += item
+                        
+                results.append(postprocessed_result)
 
         # assert check_return_type(results)
         return results
@@ -1581,7 +1597,7 @@
             d = ModelDownloader()
             kwargs.update(**d.download_and_unpack(model_tag))
         
-        return Speech2Text(**kwargs)
+        return Speech2TextTransducer(**kwargs)
 
 
 class Speech2TextSAASR:

--
Gitblit v1.9.1