From 741d089eb9dd9be7b6e2cabbd40fc0a784eb38f3 Mon Sep 17 00:00:00 2001
From: 游雁 <zhifu.gzf@alibaba-inc.com>
Date: 星期三, 21 二月 2024 16:28:58 +0800
Subject: [PATCH] Merge branch 'main' of github.com:alibaba-damo-academy/FunASR merge

---
 funasr/auto/auto_model.py |   45 ++++++++++++++++++++++++++++++---------------
 1 files changed, 30 insertions(+), 15 deletions(-)

diff --git a/funasr/auto/auto_model.py b/funasr/auto/auto_model.py
index e4a154d..e5faa2a 100644
--- a/funasr/auto/auto_model.py
+++ b/funasr/auto/auto_model.py
@@ -1,14 +1,13 @@
 import json
 import time
+import copy
 import torch
-import hydra
 import random
 import string
 import logging
 import os.path
 import numpy as np
 from tqdm import tqdm
-from omegaconf import DictConfig, OmegaConf, ListConfig
 
 from funasr.register import tables
 from funasr.utils.load_utils import load_bytes
@@ -17,7 +16,7 @@
 from funasr.utils.vad_utils import slice_padding_audio_samples
 from funasr.train_utils.set_all_random_seed import set_all_random_seed
 from funasr.train_utils.load_pretrained_model import load_pretrained_model
-from funasr.utils.load_utils import load_audio_text_image_video, extract_fbank
+from funasr.utils.load_utils import load_audio_text_image_video
 from funasr.utils.timestamp_tools import timestamp_sentence
 from funasr.models.campplus.utils import sv_chunk, postprocess, distribute_spk
 try:
@@ -380,16 +379,22 @@
                             result[k] = restored_data[j][k]
                         else:
                             result[k] += restored_data[j][k]
-                            
+            
+            return_raw_text = kwargs.get('return_raw_text', False)            
             # step.3 compute punc model
             if self.punc_model is not None:
                 self.punc_kwargs.update(cfg)
                 punc_res = self.inference(result["text"], model=self.punc_model, kwargs=self.punc_kwargs, disable_pbar=True, **cfg)
-                import copy; raw_text = copy.copy(result["text"])
+                raw_text = copy.copy(result["text"])
+                if return_raw_text: result['raw_text'] = raw_text
                 result["text"] = punc_res[0]["text"]
+            else:
+                raw_text = None
                 
             # speaker embedding cluster after resorted
             if self.spk_model is not None and kwargs.get('return_spk_res', True):
+                if raw_text is None:
+                    logging.error("Missing punc_model, which is required by spk_model.")
                 all_segments = sorted(all_segments, key=lambda x: x[0])
                 spk_embedding = result['spk_embedding']
                 labels = self.cb_model(spk_embedding.cpu(), oracle_num=kwargs.get('preset_spk_num', None))
@@ -398,20 +403,30 @@
                 if self.spk_mode == 'vad_segment':  # recover sentence_list
                     sentence_list = []
                     for res, vadsegment in zip(restored_data, vadsegments):
-                        sentence_list.append({"start": vadsegment[0],\
-                                                "end": vadsegment[1],
-                                                "sentence": res['text'],
-                                                "timestamp": res['timestamp']})
+                        if 'timestamp' not in res:
+                            logging.error("Only 'iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch' \
+                                           and 'iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'\
+                                           can predict timestamp, and speaker diarization relies on timestamps.")
+                        sentence_list.append({"start": vadsegment[0],
+                                              "end": vadsegment[1],
+                                              "sentence": res['text'],
+                                              "timestamp": res['timestamp']})
                 elif self.spk_mode == 'punc_segment':
-                    sentence_list = timestamp_sentence(punc_res[0]['punc_array'], \
-                                                        result['timestamp'], \
-                                                        result['text'])
+                    if 'timestamp' not in result:
+                        logging.error("Only 'iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch' \
+                                       and 'iic/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch'\
+                                       can predict timestamp, and speaker diarization relies on timestamps.")
+                    sentence_list = timestamp_sentence(punc_res[0]['punc_array'],
+                                                       result['timestamp'],
+                                                       raw_text,
+                                                       return_raw_text=return_raw_text)
                 distribute_spk(sentence_list, sv_output)
                 result['sentence_info'] = sentence_list
             elif kwargs.get("sentence_timestamp", False):
-                sentence_list = timestamp_sentence(punc_res[0]['punc_array'], \
-                                                        result['timestamp'], \
-                                                        result['text'])
+                sentence_list = timestamp_sentence(punc_res[0]['punc_array'],
+                                                   result['timestamp'],
+                                                   raw_text,
+                                                   return_raw_text=return_raw_text)
                 result['sentence_info'] = sentence_list
             if "spk_embedding" in result: del result['spk_embedding']
                     

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