Add endpointing (#54)

sherpa-onnx/python/sherpa_onnx/online_recognizer.py

@@ -2,12 +2,13 @@ from pathlib import Path
 from typing import List
 
 from _sherpa_onnx import (
+    EndpointConfig,
+    FeatureExtractorConfig,
+    OnlineRecognizer as _Recognizer,
+    OnlineRecognizerConfig,
     OnlineStream,
     OnlineTransducerModelConfig,
-    FeatureExtractorConfig,
-    OnlineRecognizerConfig,
 )
-from _sherpa_onnx import OnlineRecognizer as _Recognizer
 
 
 def _assert_file_exists(f: str):
@@ -26,6 +27,10 @@ class OnlineRecognizer(object):
         num_threads: int = 4,
         sample_rate: float = 16000,
         feature_dim: int = 80,
+        enable_endpoint_detection: bool = False,
+        rule1_min_trailing_silence: int = 2.4,
+        rule2_min_trailing_silence: int = 1.2,
+        rule3_min_utterance_length: int = 20,
     ):
         """
         Please refer to
@@ -52,6 +57,22 @@ class OnlineRecognizer(object):
             Sample rate of the training data used to train the model.
           feature_dim:
             Dimension of the feature used to train the model.
+          enable_endpoint_detection:
+            True to enable endpoint detection. False to disable endpoint
+            detection.
+          rule1_min_trailing_silence:
+            Used only when enable_endpoint_detection is True. If the duration
+            of trailing silence in seconds is larger than this value, we assume
+            an endpoint is detected.
+          rule2_min_trailing_silence:
+            Used only when enable_endpoint_detection is True. If we have decoded
+            something that is nonsilence and if the duration of trailing silence
+            in seconds is larger than this value, we assume an endpoint is
+            detected.
+          rule3_min_utterance_length:
+            Used only when enable_endpoint_detection is True. If the utterance
+            length in seconds is larger than this value, we assume an endpoint
+            is detected.
         """
         _assert_file_exists(tokens)
         _assert_file_exists(encoder)
@@ -72,10 +93,18 @@ class OnlineRecognizer(object):
             feature_dim=feature_dim,
         )
 
+        endpoint_config = EndpointConfig(
+            rule1_min_trailing_silence=rule1_min_trailing_silence,
+            rule2_min_trailing_silence=rule2_min_trailing_silence,
+            rule3_min_utterance_length=rule3_min_utterance_length,
+        )
+
         recognizer_config = OnlineRecognizerConfig(
             feat_config=feat_config,
             model_config=model_config,
             tokens=tokens,
+            endpoint_config=endpoint_config,
+            enable_endpoint=enable_endpoint_detection,
         )
 
         self.recognizer = _Recognizer(recognizer_config)
@@ -93,4 +122,10 @@ class OnlineRecognizer(object):
         return self.recognizer.is_ready(s)
 
     def get_result(self, s: OnlineStream) -> str:
-        return self.recognizer.get_result(s).text
+        return self.recognizer.get_result(s).text.strip()
+
+    def is_endpoint(self, s: OnlineStream) -> bool:
+        return self.recognizer.is_endpoint(s)
+
+    def reset(self, s: OnlineStream) -> bool:
+        return self.recognizer.reset(s)