mirror of
https://github.com/dscripka/openWakeWord.git
synced 2026-08-27 18:17:20 -04:00
58 lines
No EOL
1.7 KiB
Python
58 lines
No EOL
1.7 KiB
Python
# Copyright 2022 David Scripka. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Imports
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import os
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import plotext as plt
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import sounddevice
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import numpy as np
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from openwakeword.model import Model
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# Get microphone stream
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mic_stream = sounddevice.InputStream(
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samplerate=16000,
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blocksize=1280,
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device = 3,
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dtype = np.int16,
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)
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# Load openwakeword model(s)
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model_name = "alexa_v5"
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model = Model(
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wakeword_model_paths=[os.path.join("../", "openwakeword", "resources", "models", model_name + ".onnx")],
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)
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# Run capture loop, checking for hotwords
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if __name__ == "__main__":
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# Start the mic stream
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mic_stream.start()
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# Create a prediction buffer
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prediction_buffer = [0]*30
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while True:
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# Get audio
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audio, overflowed = mic_stream.read(1280)
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audio = audio.squeeze()
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# Feed to openWakeWord model
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prediction = model.predict(audio)
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prediction_buffer = prediction_buffer[1:] + [round(prediction[model_name], 2)]
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# Plot predictions in graph
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plt.cld()
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plt.clt()
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plt.plot(prediction_buffer)
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plt.ylim(0,1)
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plt.show()
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plt.sleep(0.005) |