Common Voice Gender Detection 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. [!note] Wav2Vec2: Self Supervised Learning for Speech Recognition : https://arxiv.org/pdf/2006.11477 Label Space: 2 Classes Install Dependencies Inference Code Demo Inference [!note] male [!note] female Intended Use Common Voice Gender Detection is designed for: Speech Analytics – Assist in analyzing speaker demographics in call centers or customer service recordings. Conversational AI Personalization – Adjust tone or dialogue based on gender detection for more personalized voice assistants. Voice Dataset Curation – Automatically tag or filter voice datasets by speaker gender for better dataset management. Research Applications – Enable linguistic and acoustic research involving gender specific speech patterns. Multimedia Content Tagging – Automate metadata generation for gender identification in podcasts, interviews, or video content.
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