Initial commit: FunASR Speech Recognition Toolkit

Add complete FunASR codebase including models, runtime, and documentation.
2026-07-09 22:38:58 +08:00
commit 6116b1f3c6
3683 changed files with 990984 additions and 0 deletions
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+#!/usr/bin/env python3
+"""Test FSMN-VAD Streaming: chunk-by-chunk voice activity detection"""
+import sys
+import time
+import os
+
+def main():
+    import soundfile
+    from funasr import AutoModel
+
+    print("[FSMN-VAD-Streaming] Loading model...")
+    t0 = time.time()
+    model = AutoModel(
+        model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch",
+        device="cpu",
+        disable_update=True,
+        disable_pbar=True,
+    )
+    print("[FSMN-VAD-Streaming] Model loaded in %.1fs" % (time.time() - t0))
+
+    wav_file = os.path.join(model.model_path, "example/vad_example.wav")
+    speech, sample_rate = soundfile.read(wav_file)
+    chunk_size = 200  # ms
+    chunk_stride = int(chunk_size * sample_rate / 1000)
+
+    total_chunk_num = int((len(speech) - 1) / chunk_stride + 1)
+    print("[FSMN-VAD-Streaming] Audio: %.2fs, %d chunks of %dms" % (
+        len(speech) / sample_rate, total_chunk_num, chunk_size))
+
+    print("[FSMN-VAD-Streaming] Running streaming inference...")
+    t0 = time.time()
+
+    cache = {}
+    all_events = []
+    for i in range(total_chunk_num):
+        speech_chunk = speech[i * chunk_stride:(i + 1) * chunk_stride]
+        is_final = i == total_chunk_num - 1
+        res = model.generate(
+            input=speech_chunk,
+            cache=cache,
+            is_final=is_final,
+            chunk_size=chunk_size,
+        )
+        if res[0]["value"]:
+            all_events.extend(res[0]["value"])
+
+    print("[FSMN-VAD-Streaming] Inference done in %.1fs" % (time.time() - t0))
+
+    # Parse streaming VAD events into complete segments
+    # Streaming output: [beg, -1] = speech start, [-1, end] = speech end, [beg, end] = complete
+    complete_segments = []
+    pending_start = None
+    for event in all_events:
+        if event[0] >= 0 and event[1] == -1:
+            pending_start = event[0]
+        elif event[0] == -1 and event[1] >= 0:
+            if pending_start is not None:
+                complete_segments.append([pending_start, event[1]])
+                pending_start = None
+        elif event[0] >= 0 and event[1] >= 0:
+            complete_segments.append(event)
+
+    print("[FSMN-VAD-Streaming] Raw events: %d, Complete segments: %d" % (
+        len(all_events), len(complete_segments)))
+    print("[FSMN-VAD-Streaming] Segments: %s" % complete_segments)
+
+    if not complete_segments:
+        print("[FSMN-VAD-Streaming] FAILED - no complete segments")
+        return 1
+
+    # Verify segments have valid ranges
+    for seg in complete_segments:
+        if seg[1] <= seg[0]:
+            print("[FSMN-VAD-Streaming] FAILED - invalid segment: %s" % seg)
+            return 1
+
+    # Verify consistency: run again with fresh cache
+    cache2 = {}
+    all_events2 = []
+    for i in range(total_chunk_num):
+        speech_chunk = speech[i * chunk_stride:(i + 1) * chunk_stride]
+        is_final = i == total_chunk_num - 1
+        res = model.generate(
+            input=speech_chunk, cache=cache2, is_final=is_final, chunk_size=chunk_size,
+        )
+        if res[0]["value"]:
+            all_events2.extend(res[0]["value"])
+
+    if all_events != all_events2:
+        print("[FSMN-VAD-Streaming] FAILED - inconsistent across sessions")
+        return 1
+
+    print("[FSMN-VAD-Streaming] Consistency: 2 sessions identical")
+    print("[FSMN-VAD-Streaming] PASSED")
+    return 0
+
+if __name__ == "__main__":
+    sys.exit(main())