@@ -481,7 +481,7 @@ def predict(tensor):
481481#
482482
483483
484- def record_colab (seconds = 1 ):
484+ def record (seconds = 1 ):
485485
486486 from google .colab import output as colab_output
487487 from base64 import b64decode
@@ -524,35 +524,11 @@ def record_colab(seconds=1):
524524 return torchaudio .load (filename )
525525
526526
527- def record_noncolab (seconds = 1 ):
528-
529- import sounddevice
530- import scipy .io .wavfile
531-
532- sample_rate = 44100
533-
534- print (f"Recording started for { seconds } seconds." )
535- myrecording = sounddevice .rec (
536- int (seconds * sample_rate ), samplerate = sample_rate , channels = 1
537- )
538- sounddevice .wait ()
539- print ("Recording ended." )
540-
541- filename = "_audio.wav"
542- scipy .io .wavfile .write (filename , sample_rate , myrecording )
543- return torchaudio .load (filename )
544-
545-
546527# Detect whether notebook runs in google colab
547528if "google.colab" in sys .modules :
548- record = record_colab
549- else :
550- record = record_noncolab
551-
552-
553- waveform , sample_rate = record ()
554- print (f"Predicted: { predict (waveform )} ." )
555- ipd .Audio (waveform .numpy (), rate = sample_rate )
529+ waveform , sample_rate = record ()
530+ print (f"Predicted: { predict (waveform )} ." )
531+ ipd .Audio (waveform .numpy (), rate = sample_rate )
556532
557533
558534######################################################################
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