Formatting and spelling fixes.
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@ -26,33 +26,33 @@ def main():
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help="How real time the recording is in seconds.", type=float)
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parser.add_argument("--phrase_timeout", default=3,
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help="How much empty space between recordings before we "
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"consider it a new line in the transcription.", type=float)
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"consider it a new line in the transcription.", type=float)
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if 'linux' in platform:
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parser.add_argument("--default_microphone", default='pulse',
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help="Default microphone name for SpeechRecognition. "
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"Run this with 'list' to view available Microphones.", type=str)
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args = parser.parse_args()
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# The last time a recording was retreived from the queue.
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# The last time a recording was retrieved from the queue.
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phrase_time = None
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# Current raw audio bytes.
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last_sample = bytes()
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# Thread safe Queue for passing data from the threaded recording callback.
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data_queue = Queue()
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# We use SpeechRecognizer to record our audio because it has a nice feauture where it can detect when speech ends.
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# We use SpeechRecognizer to record our audio because it has a nice feature where it can detect when speech ends.
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recorder = sr.Recognizer()
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recorder.energy_threshold = args.energy_threshold
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# Definitely do this, dynamic energy compensation lowers the energy threshold dramtically to a point where the SpeechRecognizer never stops recording.
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# Definitely do this, dynamic energy compensation lowers the energy threshold dramatically to a point where the SpeechRecognizer never stops recording.
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recorder.dynamic_energy_threshold = False
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# Important for linux users.
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# Important for linux users.
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# Prevents permanent application hang and crash by using the wrong Microphone
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if 'linux' in platform:
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mic_name = args.default_microphone
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if not mic_name or mic_name == 'list':
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print("Available microphone devices are: ")
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for index, name in enumerate(sr.Microphone.list_microphone_names()):
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print(f"Microphone with name \"{name}\" found")
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print(f"Microphone with name \"{name}\" found")
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return
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else:
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for index, name in enumerate(sr.Microphone.list_microphone_names()):
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@ -61,7 +61,7 @@ def main():
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break
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else:
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source = sr.Microphone(sample_rate=16000)
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# Load / Download model
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model = args.model
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if args.model != "large" and not args.non_english:
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@ -73,13 +73,13 @@ def main():
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temp_file = NamedTemporaryFile().name
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transcription = ['']
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with source:
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recorder.adjust_for_ambient_noise(source)
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def record_callback(_, audio:sr.AudioData) -> None:
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"""
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Threaded callback function to recieve audio data when recordings finish.
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Threaded callback function to receive audio data when recordings finish.
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audio: An AudioData containing the recorded bytes.
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"""
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# Grab the raw bytes and push it into the thread safe queue.
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@ -124,7 +124,7 @@ def main():
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result = audio_model.transcribe(temp_file, fp16=torch.cuda.is_available())
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text = result['text'].strip()
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# If we detected a pause between recordings, add a new item to our transcripion.
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# If we detected a pause between recordings, add a new item to our transcription.
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# Otherwise edit the existing one.
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if phrase_complete:
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transcription.append(text)
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@ -149,4 +149,4 @@ def main():
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if __name__ == "__main__":
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main()
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main()
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