fix the websocket chunk edge bug, test=doc

paddlespeech/server/engine/asr/online/asr_engine.py

@@ -60,9 +60,9 @@ pretrained_models = {
     },
     "conformer2online_aishell-zh-16k": {
         'url':
-        'https://paddlespeech.bj.bcebos.com/s2t/multi_cn/asr1/asr1_chunk_conformer_multi_cn_ckpt_0.2.1.model.tar.gz',
+        'https://paddlespeech.bj.bcebos.com/s2t/multi_cn/asr1/asr1_chunk_conformer_multi_cn_ckpt_0.2.3.model.tar.gz',
         'md5':
-        'b450d5dfaea0ac227c595ce58d18b637',
+        '0ac93d390552336f2a906aec9e33c5fa',
         'cfg_path':
         'model.yaml',
         'ckpt_path':
@@ -78,12 +78,19 @@ pretrained_models = {
     },
 }
 
-# ASR server connection process class
 
+# ASR server connection process class
 class PaddleASRConnectionHanddler:
     def __init__(self, asr_engine):
+        """Init a Paddle ASR Connection Handler instance
+
+        Args:
+            asr_engine (ASREngine): the global asr engine
+        """
         super().__init__()
-        logger.info("create an paddle asr connection handler to process the websocket connection")
+        logger.info(
+            "create an paddle asr connection handler to process the websocket connection"
+        )
         self.config = asr_engine.config
         self.model_config = asr_engine.executor.config
         self.model = asr_engine.executor.model
@@ -105,14 +112,16 @@ class PaddleASRConnectionHanddler:
             # tokens to text
             self.text_feature = self.asr_engine.executor.text_feature
 
-            # ctc decoding
+            # ctc decoding config
             self.ctc_decode_config = self.asr_engine.executor.config.decode
             self.searcher = CTCPrefixBeamSearch(self.ctc_decode_config)
 
-            # extract fbank
+            # extract feat, new only fbank in conformer model
             self.preprocess_conf = self.model_config.preprocess_config
             self.preprocess_args = {"train": False}
             self.preprocessing = Transformation(self.preprocess_conf)
+
+            # frame window samples length and frame shift samples length
             self.win_length = self.preprocess_conf.process[0]['win_length']
             self.n_shift = self.preprocess_conf.process[0]['n_shift']
 
@@ -141,15 +150,17 @@ class PaddleASRConnectionHanddler:
                 return 0
 
             # fbank
-            x_chunk = self.preprocessing(self.remained_wav, **self.preprocess_args)
+            x_chunk = self.preprocessing(self.remained_wav,
+                                         **self.preprocess_args)
             x_chunk = paddle.to_tensor(
                 x_chunk, dtype="float32").unsqueeze(axis=0)
             if self.cached_feat is None:
                 self.cached_feat = x_chunk
             else:
-                assert(len(x_chunk.shape) == 3)
-                assert(len(self.cached_feat.shape) == 3)
-                self.cached_feat = paddle.concat([self.cached_feat, x_chunk], axis=1)
+                assert (len(x_chunk.shape) == 3)
+                assert (len(self.cached_feat.shape) == 3)
+                self.cached_feat = paddle.concat(
+                    [self.cached_feat, x_chunk], axis=1)
 
             # set the feat device
             if self.device is None:
@@ -218,15 +229,21 @@ class PaddleASRConnectionHanddler:
             return
 
         num_frames = self.cached_feat.shape[1]
-        logger.info(f"Required decoding window {decoding_window} frames, and the connection has {num_frames} frames")
+        logger.info(
+            f"Required decoding window {decoding_window} frames, and the connection has {num_frames} frames"
+        )
 
         # the cached feat must be larger decoding_window
         if num_frames < decoding_window and not is_finished:
-            logger.info(f"frame feat num is less than {decoding_window}, please input more pcm data")
+            logger.info(
+                f"frame feat num is less than {decoding_window}, please input more pcm data"
+            )
             return None, None
 
         if num_frames < context:
-            logger.info("flast {num_frames} is less than context {context} frames, and we cannot do model forward")
+            logger.info(
+                "flast {num_frames} is less than context {context} frames, and we cannot do model forward"
+            )
             return None, None
 
         logger.info("start to do model forward")
@@ -258,14 +275,11 @@ class PaddleASRConnectionHanddler:
             # update the offset
             self.offset += y.shape[1]
 
-        logger.info(f"output size: {len(outputs)}")
         ys = paddle.cat(outputs, 1)
         if self.encoder_out is None:
             self.encoder_out = ys
         else:
             self.encoder_out = paddle.concat([self.encoder_out, ys], axis=1)
-        # masks = paddle.ones([1, ys.shape[1]], dtype=paddle.bool)
-        # masks = masks.unsqueeze(1)
 
         # get the ctc probs
         ctc_probs = self.model.ctc.log_softmax(ys)  # (1, maxlen, vocab_size)
@@ -274,18 +288,17 @@ class PaddleASRConnectionHanddler:
         self.searcher.search(None, ctc_probs, self.cached_feat.place)
 
         self.hyps = self.searcher.get_one_best_hyps()
-
-        # remove the processed feat
-        if end == num_frames:
-            self.cached_feat = None 
-        else:
         assert self.cached_feat.shape[0] == 1
         assert end >= cached_feature_num
-            self.cached_feat = self.cached_feat[0,end - cached_feature_num:,:].unsqueeze(0)
-            assert len(self.cached_feat.shape) == 3, f"current cache feat shape is: {self.cached_feat.shape}"
+        self.cached_feat = self.cached_feat[0, end -
+                                            cached_feature_num:, :].unsqueeze(0)
+        assert len(
+            self.cached_feat.shape
+        ) == 3, f"current cache feat shape is: {self.cached_feat.shape}"
 
-        # ys for rescoring
-        # return ys, masks
+        logger.info(
+            f"This connection handler encoder out shape: {self.encoder_out.shape}"
+        )
 
     def update_result(self):
         logger.info("update the final result")
@@ -363,8 +376,6 @@ class PaddleASRConnectionHanddler:
         logger.info(f"best index: {best_index}")
         self.hyps = [hyps[best_index][0]]
         self.update_result()
-        # return hyps[best_index][0]
-
 
 
 class ASRServerExecutor(ASRExecutor):
@@ -409,9 +420,9 @@ class ASRServerExecutor(ASRExecutor):
             logger.info(f"Load the pretrained model, tag = {tag}")
             res_path = self._get_pretrained_path(tag)  # wenetspeech_zh
             self.res_path = res_path
-            self.cfg_path = "/home/users/xiongxinlei/task/paddlespeech-develop/PaddleSpeech/examples/aishell/asr1/model.yaml"
-            # self.cfg_path = os.path.join(res_path,
-            #                              pretrained_models[tag]['cfg_path'])
+
+            self.cfg_path = os.path.join(res_path,
+                                         pretrained_models[tag]['cfg_path'])
 
             self.am_model = os.path.join(res_path,
                                          pretrained_models[tag]['model'])

paddlespeech/server/ws/asr_socket.py

@@ -96,7 +96,6 @@ async def websocket_endpoint(websocket: WebSocket):
                 asr_results = connection_handler.get_result()
 
                 resp = {'asr_results': asr_results}
-                print("\n")
                 await websocket.send_json(resp)
     except WebSocketDisconnect:
         pass