Add C API for punctuation (#768)

2024-04-14 19:02:34 +08:00
parent b0265b258d
commit 13730ecbd8
13 changed files with 302 additions and 12 deletions
--- a/python-api-examples/streaming-paraformer-asr-microphone.py
+++ b/python-api-examples/streaming-paraformer-asr-microphone.py
@@ -0,0 +1,105 @@
+#!/usr/bin/env python3
+
+# Real-time speech recognition from a microphone with sherpa-onnx Python API
+# with endpoint detection.
+# This script uses a streaming paraformer
+#
+# Please refer to
+# https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/paraformer-models.html#
+# to download pre-trained models
+
+import sys
+from pathlib import Path
+
+try:
+    import sounddevice as sd
+except ImportError:
+    print("Please install sounddevice first. You can use")
+    print()
+    print("  pip install sounddevice")
+    print()
+    print("to install it")
+    sys.exit(-1)
+
+import sherpa_onnx
+
+
+def assert_file_exists(filename: str):
+    assert Path(filename).is_file(), (
+        f"{filename} does not exist!\n"
+        "Please refer to "
+        "https://k2-fsa.github.io/sherpa/onnx/pretrained_models/online-paraformer/paraformer-models.html to download it"
+    )
+
+
+def create_recognizer():
+    encoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/encoder.int8.onnx"
+    decoder = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/decoder.int8.onnx"
+    tokens = "./sherpa-onnx-streaming-paraformer-bilingual-zh-en/tokens.txt"
+    assert_file_exists(encoder)
+    assert_file_exists(decoder)
+    assert_file_exists(tokens)
+    recognizer = sherpa_onnx.OnlineRecognizer.from_paraformer(
+        tokens=tokens,
+        encoder=encoder,
+        decoder=decoder,
+        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
+    )
+    return recognizer
+
+
+def main():
+    devices = sd.query_devices()
+    if len(devices) == 0:
+        print("No microphone devices found")
+        sys.exit(0)
+
+    print(devices)
+    default_input_device_idx = sd.default.device[0]
+    print(f'Use default device: {devices[default_input_device_idx]["name"]}')
+
+    recognizer = create_recognizer()
+    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
+
+    stream = recognizer.create_stream()
+
+    last_result = ""
+    segment_id = 0
+    with sd.InputStream(channels=1, dtype="float32", samplerate=sample_rate) as s:
+        while True:
+            samples, _ = s.read(samples_per_read)  # a blocking read
+            samples = samples.reshape(-1)
+            stream.accept_waveform(sample_rate, samples)
+            while recognizer.is_ready(stream):
+                recognizer.decode_stream(stream)
+
+            is_endpoint = recognizer.is_endpoint(stream)
+
+            result = recognizer.get_result(stream)
+
+            if result and (last_result != result):
+                last_result = result
+                print("\r{}:{}".format(segment_id, result), end="", flush=True)
+            if is_endpoint:
+                if result:
+                    print("\r{}:{}".format(segment_id, result), flush=True)
+                    segment_id += 1
+                recognizer.reset(stream)
+
+
+if __name__ == "__main__":
+    try:
+        main()
+    except KeyboardInterrupt:
+        print("\nCaught Ctrl + C. Exiting")