Gender Ambiguous

Research on gender-ambiguous voices focuses on creating synthetic speech that avoids clear gender categorization, aiming to improve inclusivity and privacy in applications like voice assistants and speech recognition. Current efforts utilize techniques like voice morphing, pitch shifting, and generative adversarial networks (GANs) to manipulate vocal timbre and speaking style, often leveraging latent speaker embeddings to generate diverse, ambiguous voices across multiple languages. This work challenges traditional binary gender classifications in speech processing, impacting fields ranging from human-computer interaction to privacy-preserving technologies by offering more representative and inclusive voice interfaces.