update readme, fix seaco bug

README.md

@@ -90,12 +90,15 @@ Notes: Support recognition of single audio file, as well as file list in Kaldi-s
 ### Speech Recognition (Non-streaming)
 ```python
 from funasr import AutoModel
-
+# paraformer-zh is a multi-functional asr model
-model = AutoModel(model="paraformer-zh")
+# use vad, punc, spk or not as you need
-# for the long duration wav, you could add vad model
+model = AutoModel(model="paraformer-zh", model_revision="v2.0.2", \
-# model = AutoModel(model="paraformer-zh", vad_model="fsmn-vad", punc_model="ct-punc")
+                  vad_model="fsmn-vad", vad_model_revision="v2.0.2", \
-
+                  punc_model="ct-punc-c", punc_model_revision="v2.0.2", \
-res = model(input="asr_example_zh.wav", batch_size=64)
+                  spk_model="cam++", spk_model_revision="v2.0.2")
+res = model(input=f"{model.model_path}/example/asr_example.wav", 
+            batch_size=16, 
+            hotword='魔搭')
 print(res)
 ```
 Note: `model_hub`: represents the model repository, `ms` stands for selecting ModelScope download, `hf` stands for selecting Huggingface download.
@@ -108,7 +111,7 @@ chunk_size = [0, 10, 5] #[0, 10, 5] 600ms, [0, 8, 4] 480ms
 encoder_chunk_look_back = 4 #number of chunks to lookback for encoder self-attention
 decoder_chunk_look_back = 1 #number of encoder chunks to lookback for decoder cross-attention
 
-model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.0")
+model = AutoModel(model="paraformer-zh-streaming", model_revision="v2.0.2")
 
 import soundfile
 import os
@@ -163,7 +166,7 @@ for i in range(total_chunk_num):
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="ct-punc", model_revision="v2.0.1")
+model = AutoModel(model="ct-punc", model_revision="v2.0.2")
 
 res = model(input="那今天的会就到这里吧 happy new year 明年见")
 print(res)
@@ -172,7 +175,7 @@ print(res)
 ```python
 from funasr import AutoModel
 
-model = AutoModel(model="fa-zh", model_revision="v2.0.0")
+model = AutoModel(model="fa-zh", model_revision="v2.0.2")
 
 wav_file = f"{model.model_path}/example/asr_example.wav"
 text_file = f"{model.model_path}/example/asr_example.wav"

examples/industrial_data_pretraining/seaco_paraformer/demo.py

@@ -11,8 +11,10 @@ model = AutoModel(model="damo/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-co
                   vad_model_revision="v2.0.2",
                   punc_model="damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch",
                   punc_model_revision="v2.0.2",
+                  spk_model="damo/speech_campplus_sv_zh-cn_16k-common",
+                  spk_model="v2.0.2",
                   )
 
-res = model(input="https://isv-data.oss-cn-hangzhou.aliyuncs.com/ics/MaaS/ASR/test_audio/asr_example_zh.wav",
+res = model(input=f"{model.model_path}/example/asr_example.wav",
-            hotword='达摩院 磨搭')
+            hotword='达摩院 魔搭')
 print(res)

funasr/download/name_maps_from_hub.py

@@ -1,14 +1,13 @@
-
-
 name_maps_ms = {
-    "paraformer-zh": "damo/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
+    "paraformer-zh": "damo/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch",
-    "paraformer-zh-spk": "damo/speech_paraformer-large-vad-punc-spk_asr_nat-zh-cn",
     "paraformer-en": "damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020",
     "paraformer-en-spk": "damo/speech_paraformer-large-vad-punc_asr_nat-en-16k-common-vocab10020",
     "paraformer-zh-streaming": "damo/speech_paraformer-large_asr_nat-zh-cn-16k-common-vocab8404-online",
     "fsmn-vad": "damo/speech_fsmn_vad_zh-cn-16k-common-pytorch",
     "ct-punc": "damo/punc_ct-transformer_cn-en-common-vocab471067-large",
+    "ct-punc-c": "damo/punc_ct-transformer_zh-cn-common-vocab272727-pytorch",
     "fa-zh": "damo/speech_timestamp_prediction-v1-16k-offline",
+    "cam++": "damo/speech_campplus_sv_zh-cn_16k-common",
 }
 
 name_maps_hf = {

funasr/models/ct_transformer/model.py

@@ -344,7 +344,6 @@ class CTTransformer(torch.nn.Module):
                 punc_array = punctuations
             else:
                 punc_array = torch.cat([punc_array, punctuations], dim=0)
-        
         result_i = {"key": key[0], "text": new_mini_sentence_out, "punc_array": punc_array}
         results.append(result_i)
     

funasr/models/seaco_paraformer/model.py

@@ -212,7 +212,7 @@ class SeacoParaformer(BiCifParaformer, Paraformer):
                                ys_pad_lens, 
                                hw_list,
                                nfilter=50,
-                                 seaco_weight=1.0):
+                               seaco_weight=1.0):
         # decoder forward
         decoder_out, decoder_hidden, _ = self.decoder(encoder_out, encoder_out_lens, sematic_embeds, ys_pad_lens, return_hidden=True, return_both=True)
         decoder_pred = torch.log_softmax(decoder_out, dim=-1)
@@ -254,10 +254,9 @@ class SeacoParaformer(BiCifParaformer, Paraformer):
             
             dha_output = self.hotword_output_layer(merged)  # remove the last token in loss calculation
             dha_pred = torch.log_softmax(dha_output, dim=-1)
-            # import pdb; pdb.set_trace()
             def _merge_res(dec_output, dha_output):
                 lmbd = torch.Tensor([seaco_weight] * dha_output.shape[0])
-                dha_ids = dha_output.max(-1)[-1][0]
+                dha_ids = dha_output.max(-1)[-1]# [0]
                 dha_mask = (dha_ids == 8377).int().unsqueeze(-1)
                 a = (1 - lmbd) / lmbd
                 b = 1 / lmbd
@@ -267,6 +266,7 @@ class SeacoParaformer(BiCifParaformer, Paraformer):
                 logits = dec_output * dha_mask + dha_output[:,:,:] * (1-dha_mask)
                 return logits
             merged_pred = _merge_res(decoder_pred, dha_pred)
+            # import pdb; pdb.set_trace()
             return merged_pred
         else:
             return decoder_pred