Add C++ and Python API for FireRedASR AED models (#1867)

2025-02-16 22:45:24 +08:00
parent 2337169ee2
commit 316424b382
20 changed files with 1019 additions and 26 deletions
--- a/python-api-examples/offline-fire-red-asr-decode-files.py
+++ b/python-api-examples/offline-fire-red-asr-decode-files.py
@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+
+"""
+This file shows how to use a non-streaming FireRedAsr AED model from
+https://github.com/FireRedTeam/FireRedASR
+to decode files.
+
+Please download model files from
+https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+
+For instance,
+
+wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
+tar xvf sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
+rm sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16.tar.bz2
+"""
+
+from pathlib import Path
+
+import sherpa_onnx
+import soundfile as sf
+
+
+def create_recognizer():
+    encoder = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/encoder.int8.onnx"
+    decoder = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/decoder.int8.onnx"
+    tokens = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/tokens.txt"
+    test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/0.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/1.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/2.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/3.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/8k.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/3-sichuan.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/4-tianjin.wav"
+    #  test_wav = "./sherpa-onnx-fire-red-asr-large-zh_en-2025-02-16/test_wavs/5-henan.wav"
+
+    if (
+        not Path(encoder).is_file()
+        or not Path(decoder).is_file()
+        or not Path(test_wav).is_file()
+    ):
+        raise ValueError(
+            """Please download model files from
+            https://github.com/k2-fsa/sherpa-onnx/releases/tag/asr-models
+            """
+        )
+    return (
+        sherpa_onnx.OfflineRecognizer.from_fire_red_asr(
+            encoder=encoder,
+            decoder=decoder,
+            tokens=tokens,
+            debug=True,
+        ),
+        test_wav,
+    )
+
+
+def main():
+    recognizer, wave_filename = create_recognizer()
+
+    audio, sample_rate = sf.read(wave_filename, dtype="float32", always_2d=True)
+    audio = audio[:, 0]  # only use the first channel
+
+    # audio is a 1-D float32 numpy array normalized to the range [-1, 1]
+    # sample_rate does not need to be 16000 Hz
+
+    stream = recognizer.create_stream()
+    stream.accept_waveform(sample_rate, audio)
+    recognizer.decode_stream(stream)
+    print(wave_filename)
+    print(stream.result)
+
+
+if __name__ == "__main__":
+    main()