# Why I'm getting same result with or without using Wav2Vec2Processor?

**URL:** <https://discuss.huggingface.co/t/why-im-getting-same-result-with-or-without-using-wav2vec2processor/32482>\
**Category:** 🤗Tokenizers\
**Created:** [February 25, 2023, 3:56am UTC](https://discuss.huggingface.co/t/why-im-getting-same-result-with-or-without-using-wav2vec2processor/32482 "2023-02-25T03:56:33Z")\
**Posts on this page:** 1\
**Page:** 1

<div class="post-metadata">

**Author:** ![laro1](https://avatars.discourse-cdn.com/v4/letter/l/ad7895/32.png) [@laro1](https://discuss.huggingface.co/u/laro1)\
**Post date:** [February 25, 2023, 3:56am UTC](https://discuss.huggingface.co/t/why-im-getting-same-result-with-or-without-using-wav2vec2processor/32482/1 "2023-02-25T03:56:33Z")

</div>

I’m running simple wav2vec2 code on short without noise voice:

```
#processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")     

FILE_NAME = "tutorial-assets/Lab41-SRI-VOiCES-src-sp0307-ch127535-sg0042.wav"
SPEECH_FILE = download_asset(FILE_NAME)

speech, sr = librosa.load(SPEECH_FILE, sr=16000)

speech = torch.tensor(speech)
speech = speech.reshape(1, -1)

logits = model(speech).logits

predicted_ids = torch.argmax(logits, dim=-1)
transcription = processor.decode(predicted_ids[0])
transcription

```

results: `'I HAD THAT CURIOSITY BESIDE ME AT THIS MOMENT'`

- As you see, I didn’t use `processor`.
- The examples on the net always used `processor`

So:

1. What is the benefit of using processor ?
2. When do we need to use it ?