add a new korean model

examples.py

@@ -58,7 +58,7 @@ examples = [
     ],
     [
         "Korean",
-        "k2-fsa/sherpa-onnx-streaming-zipformer-korean-2024-06-16",
+        "k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24",
         "greedy_search",
         4,
         "No",
@@ -423,7 +423,7 @@ examples = [
     ],
     [
         "Korean",
-        "k2-fsa/sherpa-onnx-streaming-zipformer-korean-2024-06-16",
+        "k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24",
         "greedy_search",
         4,
         "No",
@@ -431,7 +431,7 @@ examples = [
     ],
     [
         "Korean",
-        "k2-fsa/sherpa-onnx-streaming-zipformer-korean-2024-06-16",
+        "k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24",
         "greedy_search",
         4,
         "No",
@@ -439,7 +439,7 @@ examples = [
     ],
     [
         "Korean",
-        "k2-fsa/sherpa-onnx-streaming-zipformer-korean-2024-06-16",
+        "k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24",
         "greedy_search",
         4,
         "No",

model.py

@@ -297,6 +297,46 @@ def _get_aishell2_pretrained_model(
     return recognizer
 
 
+@lru_cache(maxsize=10)
+def _get_offline_pre_trained_model(
+    repo_id: str, decoding_method: str, num_active_paths: int
+) -> sherpa_onnx.OfflineRecognizer:
+    assert repo_id in ("k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24",), repo_id
+
+    encoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="encoder-epoch-99-avg-1.int8.onnx",
+        subfolder=".",
+    )
+
+    decoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="decoder-epoch-99-avg-1.onnx",
+        subfolder=".",
+    )
+
+    joiner_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="joiner-epoch-99-avg-1.onnx",
+        subfolder=".",
+    )
+
+    tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
+
+    recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
+        tokens=tokens,
+        encoder=encoder_model,
+        decoder=decoder_model,
+        joiner=joiner_model,
+        num_threads=2,
+        sample_rate=16000,
+        feature_dim=80,
+        decoding_method=decoding_method,
+    )
+
+    return recognizer
+
+
 @lru_cache(maxsize=10)
 def _get_yifan_thai_pretrained_model(
     repo_id: str, decoding_method: str, num_active_paths: int
@@ -1409,6 +1449,7 @@ cantonese_models = {
 
 korean_models = {
     "k2-fsa/sherpa-onnx-streaming-zipformer-korean-2024-06-16": _get_streaming_zipformer_pre_trained_model,
+    "k2-fsa/sherpa-onnx-zipformer-korean-2024-06-24": _get_offline_pre_trained_model,
 }
 
 thai_models = {