I would really like you to share more context, because I’m still not able to reproduce. This is on a RPi4, reinstalled right now, with the ice tower fan + heatspread:
pi@raspberrypi:~/ds $ for f in audio/*.wav; do echo $f; mediainfo $f | grep Duration; done;
audio/2830-3980-0043.wav
Duration : 1 s 975 ms
Duration : 1 s 975 ms
audio/4507-16021-0012.wav
Duration : 2 s 735 ms
Duration : 2 s 735 ms
audio/8455-210777-0068.wav
Duration : 2 s 590 ms
Duration : 2 s 590 ms
pi@raspberrypi:~/ds $ ./deepspeech --model models/output_graph.tflite --alphabet models/alphabet.txt --audio audio/ -t
TensorFlow: v1.14.0-14-g1aad02a78e
DeepSpeech: v0.6.0-alpha.5-59-ga8a7af05
INFO: Initialized TensorFlow Lite runtime.
Running on directory audio/
> audio//4507-16021-0012.wav
why should one halt on the way
cpu_time_overall=3.24553
> audio//2830-3980-0043.wav
experienced proof less
cpu_time_overall=2.38253
> audio//8455-210777-0068.wav
your power is sufficient i said
cpu_time_overall=3.23032
So it’s consistent with the previous builds I did. Can you @dr0ptp4kt give more context on what you do ? How do you build / measure ?