File size: 1,545 Bytes
8823fca |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 |
---
license: unknown
datasets:
- PolyAI/minds14
language:
- en
metrics:
- accuracy
- wer
- f1
- bleu
base_model:
- openai/whisper-tiny
pipeline_tag: automatic-speech-recognition
model-index:
- name: whisper-mind14-enUS
results:
- task:
type: ASR
dataset:
name: minds-14
type: enUS
metrics:
- name: Accuracy
type: Accuracy
value: 62.25
- task:
type: ASR
dataset:
name: minds-14
type: enUS
metrics:
- name: wer
type: wer
value: 0.38%
- task:
type: ASR
dataset:
name: minds-14
type: enUS
metrics:
- name: f1
type: f1
value: 0.6722
- task:
type: ASR
dataset:
name: minds-14
type: enUS
metrics:
- name: bleu
type: bleu
value: 0.0235
---
this model based on whisper-tiny model that trained with minds-14 dataset, only trained in english version : enUS
example of using model to classify intent:
```python
>>> from transformers import pipeline
model_id = "kairaamilanii/whisper-mind14-enUS"
transcriber = pipeline(
"automatic-speech-recognition",
model=model_id,
chunk_length_s=30,
device="cuda:0" if torch.cuda.is_available() else "cpu",
)
audio_file = "/content/602b9a90963e11ccd901cbd0.wav" # Replace with your audio file path
text = transcriber(audio_file)
text
```
example output:
```python
{'text': "hello i was looking at my recent transactions and i saw that there's a payment that i didn't make will you be able to stop this thank you"}
``` |