Create app.py

app.py is added

app.py

@@ -0,0 +1,42 @@
+from transformers import pipeline
+import torch
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+classifier = pipeline(
+    "audio-classification", model="MIT/ast-finetuned-speech-commands-v2", device=device
+)
+
+from transformers.pipelines.audio_utils import ffmpeg_microphone_live
+
+
+def launch_fn(
+    wake_word="marvin",
+    prob_threshold=0.5,
+    chunk_length_s=2.0,
+    stream_chunk_s=0.25,
+    debug=False,
+):
+    if wake_word not in classifier.model.config.label2id.keys():
+        raise ValueError(
+            f"Wake word {wake_word} not in set of valid class labels, pick a wake word in the set {classifier.model.config.label2id.keys()}."
+        )
+
+    sampling_rate = classifier.feature_extractor.sampling_rate
+
+    mic = ffmpeg_microphone_live(
+        sampling_rate=sampling_rate,
+        chunk_length_s=chunk_length_s,
+        stream_chunk_s=stream_chunk_s,
+    )
+
+    print("Listening for wake word...")
+    for prediction in classifier(mic):
+        prediction = prediction[0]
+        if debug:
+            print(prediction)
+        if prediction["label"] == wake_word:
+            if prediction["score"] > prob_threshold:
+                return True
+
+launch_fn(debug=True)