Bad inference result.

Hello, I’m trying to reproduce this issue #308 using the same audio but I’m still receiving Gibberish (ish) inferences.

Since I could not find any information on which model and which command they were using in the issue, I’m posting here the info I’m using:

# Download test audio and resample (sampling rate) to 16k

deepspeech.pytorch# wget https://dare.wiscweb.wisc.edu/wp-content/uploads/sites/1051/2008/04/Arthur.mp3
deepspeech.pytorch# sox Arthur.mp3 -c 1 -r 16000 arthur_clip.wav trim 0 15

# Running the inference on the audio clip
deepspeech.pytorch# python transcribe.py --model-path librispeech_pretrained_v2.pth --audio-path arthur_clip.wav --lm-path 3-gram.pruned.3e-7.arpa --alpha 1.65 --beta 0.35

>>>
{
    "output": [
        {
            "transcription": "THE STARY OF OWT OF THE WRAPTH ONCE UPON A TIME THERE WAS A YOUNG RAG AND CUTD IN MYE GUFF ERS MOINE WHENEVER THE HAD THE RIHT SAYES HIM IF HE WOULD LIKE TO COME OUT HUNTING BOT THEM HE WHEN ANSWER IN A HORSE"
        }
    ],
    "_meta": {
        "acoustic_model": {
            "name": "librispeech_pretrained_v2.pth"
        },
        "language_model": {
            "name": "3-gram.pruned.3e-7.arpa"
        },
        "decoder": {
            "lm": true,
            "alpha": 1.65,
            "beta": 0.35,
            "type": "greedy"
        }
    }
}

I’m using the latest release (v2) as well as its respective commit.

As you can see, those are fairly different results from the one @ryanleary got in aforementioned comment

I tested several different configurations with the different models and both 3-gram.pruned.3e-7.arpa and 3-gram.3e-7.arpa as arguments for the transcribe.py script but in every case I got weird results with those uppercase characters and random words.

Am I doing something wrong here?

[SeanNaren]

My bad, aggressive stale bot… will try to get time to reproduce/investigate

[stale[bot]]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.