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--- |
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library_name: transformers.js |
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base_model: |
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- prithivMLmods/Common-Voice-Gender-Detection |
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license: apache-2.0 |
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language: |
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- en |
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pipeline_tag: audio-classification |
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tags: |
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- Gender-Detection |
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--- |
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# Common-Voice-Gender-Detection (ONNX) |
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This is an ONNX version of [prithivMLmods/Common-Voice-Gender-Detection](https://huggingface.co/prithivMLmods/Common-Voice-Gender-Detection). It was automatically converted and uploaded using [this space](https://huggingface.co/spaces/onnx-community/convert-to-onnx). |
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> **Common-Voice-Gender-Detection** is a fine-tuned version of `facebook/wav2vec2-base-960h` for **binary audio classification**, specifically trained to detect speaker gender as **female** or **male**. This model leverages the `Wav2Vec2ForSequenceClassification` architecture for efficient and accurate voice-based gender classification. |
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> [!note] |
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Wav2Vec2: Self-Supervised Learning for Speech Recognition : [https://arxiv.org/pdf/2006.11477](https://arxiv.org/pdf/2006.11477) |
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--- |
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## Intended Use |
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`Common-Voice-Gender-Detection` is designed for: |
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* **Speech Analytics** – Assist in analyzing speaker demographics in call centers or customer service recordings. |
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* **Conversational AI Personalization** – Adjust tone or dialogue based on gender detection for more personalized voice assistants. |
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* **Voice Dataset Curation** – Automatically tag or filter voice datasets by speaker gender for better dataset management. |
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* **Research Applications** – Enable linguistic and acoustic research involving gender-specific speech patterns. |
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* **Multimedia Content Tagging** – Automate metadata generation for gender identification in podcasts, interviews, or video content. |
