File size: 2,662 Bytes
3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e 3d2bc37 5ade76e |
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 |
---
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_11_0
model-index:
- name: Whisper-small-ar
results: []
library_name: transformers
pipeline_tag: automatic-speech-recognition
---
# Arabic-Whisper Small
## Description
Whisper-small-ar is an Automatic Speech Recognition (ASR) model fine-tuned specifically for the Arabic language using the Whisper model architecture. ASR models are designed to convert spoken language into written text. This model has been fine-tuned on the Mozilla Common Voice dataset (version 11.0) to transcribe spoken Arabic speech into textual form.
### Key Features
- **Arabic Language Support:** Whisper-small-ar is optimized for recognizing and transcribing the Arabic language accurately. It can handle various Arabic dialects and accents.
- **Transformer Architecture:** The model is built on a powerful Transformer-based encoder-decoder architecture, which has demonstrated state-of-the-art performance in various natural language processing tasks, including ASR.
- **Fine-tuned for Arabic ASR:** The model has undergone a fine-tuning process on a substantial amount of Arabic speech data, making it well-suited for a wide range of ASR applications in Arabic, such as transcription of podcasts, call center recordings, and more.
- **Open-Source:** Whisper-small-ar is open-source and available for use by the research and developer community, facilitating the advancement of ASR technology for the Arabic language.
- **Compatible with Hugging Face Transformers:** You can easily integrate and utilize this model in your ASR projects using the Hugging Face Transformers library.
### Use Cases
Whisper-small-ar can be employed in a variety of ASR use cases, including:
- **Transcription Services:** Convert spoken Arabic content, such as audio recordings, podcasts, or videos, into written text for indexing, search, or translation purposes.
- **Voice Assistants:** Enhance voice-activated systems and virtual assistants with accurate Arabic speech recognition capabilities.
- **Language Processing Applications:** Integrate the model into applications involving Arabic language processing, such as sentiment analysis, keyword extraction, and more.
- **Multilingual ASR:** Combine Whisper-small-ar with other multilingual ASR models for applications requiring recognition of multiple languages.
## Usage
```python
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="ayoubkirouane/whisper-small-ar")
def transcribe(audio):
text = pipe(audio)["text"]
return text
``` |