Add Python APIs for WeNet CTC models (#428)

python-api-examples/streaming_server.py

@@ -40,10 +40,17 @@ python3 ./python-api-examples/streaming_server.py \
 
 Please refer to
 https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/index.html
+https://k2-fsa.github.io/sherpa/onnx/pretrained_models/wenet/index.html
 to download pre-trained models.
 
 The model in the above help messages is from
 https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-transducer/zipformer-transducer-models.html#csukuangfj-sherpa-onnx-streaming-zipformer-bilingual-zh-en-2023-02-20-bilingual-chinese-english
+
+To use a WeNet streaming Conformer CTC model, please use
+
+python3 ./python-api-examples/streaming_server.py \
+  --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt \
+  --wenet-ctc=./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.onnx
 """
 
 import argparse
@@ -130,6 +137,12 @@ def add_model_args(parser: argparse.ArgumentParser):
         help="Path to the transducer joiner model.",
     )
 
+    parser.add_argument(
+        "--wenet-ctc",
+        type=str,
+        help="Path to the model.onnx from WeNet",
+    )
+
     parser.add_argument(
         "--paraformer-encoder",
         type=str,
@@ -212,7 +225,6 @@ def add_hotwords_args(parser: argparse.ArgumentParser):
     )
 
 
-
 def add_modified_beam_search_args(parser: argparse.ArgumentParser):
     parser.add_argument(
         "--num-active-paths",
@@ -393,6 +405,20 @@ def create_recognizer(args) -> sherpa_onnx.OnlineRecognizer:
             rule3_min_utterance_length=args.rule3_min_utterance_length,
             provider=args.provider,
         )
+    elif args.wenet_ctc:
+        recognizer = sherpa_onnx.OnlineRecognizer.from_wenet_ctc(
+            tokens=args.tokens,
+            model=args.wenet_ctc,
+            num_threads=args.num_threads,
+            sample_rate=args.sample_rate,
+            feature_dim=args.feat_dim,
+            decoding_method=args.decoding_method,
+            enable_endpoint_detection=args.use_endpoint != 0,
+            rule1_min_trailing_silence=args.rule1_min_trailing_silence,
+            rule2_min_trailing_silence=args.rule2_min_trailing_silence,
+            rule3_min_utterance_length=args.rule3_min_utterance_length,
+            provider=args.provider,
+        )
     else:
         raise ValueError("Please provide a model")
 
@@ -727,6 +753,8 @@ def check_args(args):
         assert Path(
             args.paraformer_decoder
         ).is_file(), f"{args.paraformer_decoder} does not exist"
+    elif args.wenet_ctc:
+        assert Path(args.wenet_ctc).is_file(), f"{args.wenet_ctc} does not exist"
     else:
         raise ValueError("Please provide a model")