Year: 2026
Type: preprint
Abstract: We present MERaLiON-GR, a speech gender recognition system that performs binary classification (female / male) on English and Southeast Asian (SEA) languages. The model finetunes MERaLiON-SpeechEncoder-2, a large conformer based transformer pre-trained on a broad speech corpus, and applies parameter efficient fine-tuning via Low-Rank Adaptation (LoRA) to adapt the encoder to the gender recognition task, and appends a multi-scale ECAPA-TDNN down stream network with attention pooling and a lightweight linear classifier. Extensive evaluations across multilingual Singaporean and Southeast Asian languages (English, Chinese, Malay, Tamil, Thai, Vietnamese, Indonesian, and Khmer) show that MERaLiON-GR consistently surpasses the state-of-the-art gender recognition model Vox-Profile and a large Audio-LLM, in both full-utterance and segment level evaluation modes. The results underscore the value of dedicated speech models in achieving accurate paralinguistic understanding and strong cross-lingual generalization.
Source: arXiv (Cornell University)
Authors: Wang, Qiongqiong, Aw, Ai Ti, Chen, Nancy F., Chiu, Ying Lay, Ding, Yang, He, Yingxu, Jiang, Ridong, Liu, Zhuohan, Lu, Yanfeng, Ma, Yi, Huzaifah, Muhammad, Johan, Nabilah Binte Md, Lertcheva, Nattadaporn, Duc, Pham Minh, Bhupendra, Sailor Hardik, Salleh, Siti Umairah Binte Mohammad, Sun, Shuo, Vangani, Tarun Kumar, Wong, Jeremy H. M., Wu, Jinyang, Zhang, Longyin
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7196937800