Common-Voice-Gender-Detection (ONNX)
This is an ONNX version of prithivMLmods/Common-Voice-Gender-Detection. It was automatically converted and uploaded using this space.
Common-Voice-Gender-Detection is a fine-tuned version of
facebook/wav2vec2-base-960hfor binary audio classification, specifically trained to detect speaker gender as female or male. This model leverages theWav2Vec2ForSequenceClassificationarchitecture for efficient and accurate voice-based gender classification.
[!note] Wav2Vec2: Self-Supervised Learning for Speech Recognition : https://arxiv.org/pdf/2006.11477
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.