Code refactoring (#74)

* Don't reset model state and feature extractor on endpointing

* support passing decoding_method from commandline

* Add modified_beam_search to Python API

* fix C API example

* Fix style issues

python-api-examples/decode-file.py

@@ -53,6 +53,20 @@ def get_args():
         help="Path to the joiner model",
     )
 
+    parser.add_argument(
+        "--num-threads",
+        type=int,
+        default=1,
+        help="Number of threads for neural network computation",
+    )
+
+    parser.add_argument(
+        "--decoding-method",
+        type=str,
+        default="greedy_search",
+        help="Valid values are greedy_search and modified_beam_search",
+    )
+
     parser.add_argument(
         "--wave-filename",
         type=str,
@@ -65,7 +79,6 @@ def get_args():
 
 def main():
     sample_rate = 16000
-    num_threads = 2
 
     args = get_args()
     assert_file_exists(args.encoder)
@@ -81,9 +94,10 @@ def main():
         encoder=args.encoder,
         decoder=args.decoder,
         joiner=args.joiner,
-        num_threads=num_threads,
+        num_threads=args.num_threads,
         sample_rate=sample_rate,
         feature_dim=80,
+        decoding_method=args.decoding_method,
     )
     with wave.open(args.wave_filename) as f:
         assert f.getframerate() == sample_rate, f.getframerate()
@@ -119,7 +133,8 @@ def main():
     end_time = time.time()
     elapsed_seconds = end_time - start_time
     rtf = elapsed_seconds / duration
-    print(f"num_threads: {num_threads}")
+    print(f"num_threads: {args.num_threads}")
+    print(f"decoding_method: {args.decoding_method}")
     print(f"Wave duration: {duration:.3f} s")
     print(f"Elapsed time: {elapsed_seconds:.3f} s")
     print(f"Real time factor (RTF): {elapsed_seconds:.3f}/{duration:.3f} = {rtf:.3f}")

python-api-examples/speech-recognition-from-microphone-with-endpoint-detection.py

@@ -60,10 +60,10 @@ def get_args():
     )
 
     parser.add_argument(
-        "--wave-filename",
+        "--decoding-method",
         type=str,
-        help="""Path to the wave filename. Must be 16 kHz,
-        mono with 16-bit samples""",
+        default="greedy_search",
+        help="Valid values are greedy_search and modified_beam_search",
     )
 
     return parser.parse_args()
@@ -83,17 +83,23 @@ def create_recognizer():
         encoder=args.encoder,
         decoder=args.decoder,
         joiner=args.joiner,
+        num_threads=1,
+        sample_rate=16000,
+        feature_dim=80,
         enable_endpoint_detection=True,
         rule1_min_trailing_silence=2.4,
         rule2_min_trailing_silence=1.2,
         rule3_min_utterance_length=300,  # it essentially disables this rule
+        decoding_method=args.decoding_method,
+        max_feature_vectors=100,  # 1 second
     )
     return recognizer
 
 
 def main():
-    print("Started! Please speak")
     recognizer = create_recognizer()
+    print("Started! Please speak")
+
     sample_rate = 16000
     samples_per_read = int(0.1 * sample_rate)  # 0.1 second = 100 ms
     last_result = ""
@@ -101,6 +107,7 @@ def main():
 
     last_result = ""
     segment_id = 0
+    display = sherpa_onnx.Display(max_word_per_line=30)
     with sd.InputStream(channels=1, dtype="float32", samplerate=sample_rate) as s:
         while True:
             samples, _ = s.read(samples_per_read)  # a blocking read
@@ -115,7 +122,7 @@ def main():
 
             if result and (last_result != result):
                 last_result = result
-                print(f"{segment_id}: {result}")
+                display.print(segment_id, result)
 
             if is_endpoint:
                 if result:

python-api-examples/speech-recognition-from-microphone.py

@@ -59,10 +59,10 @@ def get_args():
     )
 
     parser.add_argument(
-        "--wave-filename",
+        "--decoding-method",
         type=str,
-        help="""Path to the wave filename. Must be 16 kHz,
-        mono with 16-bit samples""",
+        default="greedy_search",
+        help="Valid values are greedy_search and modified_beam_search",
     )
 
     return parser.parse_args()
@@ -82,9 +82,11 @@ def create_recognizer():
         encoder=args.encoder,
         decoder=args.decoder,
         joiner=args.joiner,
-        num_threads=4,
+        num_threads=1,
         sample_rate=16000,
         feature_dim=80,
+        decoding_method=args.decoding_method,
+        max_feature_vectors=100,  # 1 second
     )
     return recognizer
 
@@ -96,6 +98,7 @@ def main():
     samples_per_read = int(0.1 * sample_rate)  # 0.1 second = 100 ms
     last_result = ""
     stream = recognizer.create_stream()
+    display = sherpa_onnx.Display(max_word_per_line=40)
     with sd.InputStream(channels=1, dtype="float32", samplerate=sample_rate) as s:
         while True:
             samples, _ = s.read(samples_per_read)  # a blocking read
@@ -106,7 +109,7 @@ def main():
             result = recognizer.get_result(stream)
             if last_result != result:
                 last_result = result
-                print(result)
+                display.print(-1, result)
 
 
 if __name__ == "__main__":