us final version

voice.py

@@ -0,0 +1,72 @@
+import queue
+from collections import deque
+
+import numpy as np
+import sounddevice as sd
+import speech_recognition as sr
+
+RATE = 16000
+CHUNK = RATE // 20  # 50 ms
+CHUNK_S = CHUNK / RATE
+
+
+class NothingHeard(Exception):
+    pass
+
+
+def _rms(block):
+    return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
+
+
+def record(wait_for_speech=5.0, max_len=10.0, trailing_silence=0.9):
+    """Record from the default mic until the speaker pauses. Returns raw int16 PCM."""
+    q = queue.Queue()
+    noise = []
+    preroll = deque(maxlen=6)
+    frames = []
+    quiet = elapsed = 0.0
+
+    def on_audio(data, frames_, time_, status):
+        q.put(data[:, 0].copy())
+
+    with sd.InputStream(samplerate=RATE, channels=1, dtype="int16",
+                        blocksize=CHUNK, callback=on_audio):
+        while elapsed < max_len:
+            block = q.get(timeout=2)
+            elapsed += CHUNK_S
+            level = _rms(block)
+
+            if len(noise) < 6:
+                noise.append(level)
+                preroll.append(block)
+                continue
+            threshold = max(float(np.median(noise)) * 2.5, 250.0)
+
+            if not frames:
+                if level < threshold:
+                    preroll.append(block)
+                    if elapsed > wait_for_speech:
+                        raise NothingHeard()
+                    continue
+                frames.extend(preroll)
+
+            frames.append(block)
+            quiet = quiet + CHUNK_S if level < threshold else 0.0
+            if quiet > trailing_silence:
+                break
+
+    if not frames:
+        raise NothingHeard()
+    return np.concatenate(frames).tobytes()
+
+
+def transcribe(pcm, language):
+    audio = sr.AudioData(pcm, RATE, 2)
+    try:
+        return sr.Recognizer().recognize_google(audio, language=language)
+    except sr.UnknownValueError:
+        raise NothingHeard()
+
+
+def listen(language):
+    return transcribe(record(), language)