chore: import upstream snapshot with attribution

python/example/test_webvtt.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+
+import sys
+import subprocess
+import json
+import textwrap
+
+from webvtt import WebVTT, Caption
+from vosk import Model, KaldiRecognizer, SetLogLevel
+
+SAMPLE_RATE = 16000
+WORDS_PER_LINE = 7
+
+SetLogLevel(-1)
+
+model = Model(lang="en-us")
+rec = KaldiRecognizer(model, SAMPLE_RATE)
+rec.SetWords(True)
+
+
+def timestring(seconds):
+    minutes = seconds / 60
+    seconds = seconds % 60
+    hours = int(minutes / 60)
+    minutes = int(minutes % 60)
+    return "%i:%02i:%06.3f" % (hours, minutes, seconds)
+
+
+def transcribe():
+    command = ["ffmpeg", "-nostdin", "-loglevel", "quiet", "-i", sys.argv[1],
+               "-ar", str(SAMPLE_RATE), "-ac", "1", "-f", "s16le", "-"]
+    with subprocess.Popen(command, stdout=subprocess.PIPE) as process:
+
+        results = []
+        while True:
+            data = process.stdout.read(4000)
+            if len(data) == 0:
+                break
+            if rec.AcceptWaveform(data):
+                results.append(rec.Result())
+        results.append(rec.FinalResult())
+
+        vtt = WebVTT()
+        for _, res in enumerate(results):
+            words = json.loads(res).get("result")
+            if not words:
+                continue
+
+            start = timestring(words[0]["start"])
+            end = timestring(words[-1]["end"])
+            content = " ".join([w["word"] for w in words])
+
+            caption = Caption(start, end, textwrap.fill(content))
+            vtt.captions.append(caption)
+
+        # save or return webvtt
+        if len(sys.argv) > 2:
+            vtt.save(sys.argv[2])
+        else:
+            print(vtt.content)
+
+
+if __name__ == "__main__":
+    if not 1 < len(sys.argv) < 4:
+        print("Usage: {} audiofile [output file]".format(sys.argv[0]))
+        sys.exit(1)
+    transcribe()