Support resampling (#77)

python-api-examples/decode-file.py

@@ -78,8 +78,6 @@ def get_args():
 
 
 def main():
-    sample_rate = 16000
-
     args = get_args()
     assert_file_exists(args.encoder)
     assert_file_exists(args.decoder)
@@ -95,12 +93,16 @@ def main():
         decoder=args.decoder,
         joiner=args.joiner,
         num_threads=args.num_threads,
-        sample_rate=sample_rate,
+        sample_rate=16000,
         feature_dim=80,
         decoding_method=args.decoding_method,
     )
     with wave.open(args.wave_filename) as f:
-        assert f.getframerate() == sample_rate, f.getframerate()
+        # If the wave file has a different sampling rate from the one
+        # expected by the model (16 kHz in our case), we will do
+        # resampling inside sherpa-onnx
+        wave_file_sample_rate = f.getframerate()
+
         assert f.getnchannels() == 1, f.getnchannels()
         assert f.getsampwidth() == 2, f.getsampwidth()  # it is in bytes
         num_samples = f.getnframes()
@@ -110,17 +112,17 @@ def main():
 
         samples_float32 = samples_float32 / 32768
 
-    duration = len(samples_float32) / sample_rate
+    duration = len(samples_float32) / wave_file_sample_rate
 
     start_time = time.time()
     print("Started!")
 
     stream = recognizer.create_stream()
 
-    stream.accept_waveform(sample_rate, samples_float32)
+    stream.accept_waveform(wave_file_sample_rate, samples_float32)
 
-    tail_paddings = np.zeros(int(0.2 * sample_rate), dtype=np.float32)
-    stream.accept_waveform(sample_rate, tail_paddings)
+    tail_paddings = np.zeros(int(0.2 * wave_file_sample_rate), dtype=np.float32)
+    stream.accept_waveform(wave_file_sample_rate, tail_paddings)
 
     stream.input_finished()
 

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

@@ -100,7 +100,9 @@ def main():
     recognizer = create_recognizer()
     print("Started! Please speak")
 
-    sample_rate = 16000
+    # The model is using 16 kHz, we use 48 kHz here to demonstrate that
+    # sherpa-onnx will do resampling inside.
+    sample_rate = 48000
     samples_per_read = int(0.1 * sample_rate)  # 0.1 second = 100 ms
     last_result = ""
     stream = recognizer.create_stream()

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

@@ -92,9 +92,12 @@ def create_recognizer():
 
 
 def main():
-    print("Started! Please speak")
     recognizer = create_recognizer()
-    sample_rate = 16000
+    print("Started! Please speak")
+
+    # The model is using 16 kHz, we use 48 kHz here to demonstrate that
+    # sherpa-onnx will do resampling inside.
+    sample_rate = 48000
     samples_per_read = int(0.1 * sample_rate)  # 0.1 second = 100 ms
     last_result = ""
     stream = recognizer.create_stream()