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--- |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: openai/whisper-small |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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model-index: |
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- name: Whisper-small-ar |
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results: [] |
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library_name: transformers |
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pipeline_tag: automatic-speech-recognition |
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--- |
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# Arabic-Whisper Small |
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## Description |
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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. |
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### Key Features |
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- **Arabic Language Support:** Whisper-small-ar is optimized for recognizing and transcribing the Arabic language accurately. It can handle various Arabic dialects and accents. |
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- **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. |
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- **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. |
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- **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. |
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- **Compatible with Hugging Face Transformers:** You can easily integrate and utilize this model in your ASR projects using the Hugging Face Transformers library. |
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### Use Cases |
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Whisper-small-ar can be employed in a variety of ASR use cases, including: |
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- **Transcription Services:** Convert spoken Arabic content, such as audio recordings, podcasts, or videos, into written text for indexing, search, or translation purposes. |
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- **Voice Assistants:** Enhance voice-activated systems and virtual assistants with accurate Arabic speech recognition capabilities. |
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- **Language Processing Applications:** Integrate the model into applications involving Arabic language processing, such as sentiment analysis, keyword extraction, and more. |
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- **Multilingual ASR:** Combine Whisper-small-ar with other multilingual ASR models for applications requiring recognition of multiple languages. |
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## Usage |
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```python |
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# Use a pipeline as a high-level helper |
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from transformers import pipeline |
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pipe = pipeline("automatic-speech-recognition", model="ayoubkirouane/whisper-small-ar") |
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def transcribe(audio): |
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text = pipe(audio)["text"] |
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return text |
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``` |
