MERaLiON-GR: Speech Gender Recognition Model for English and SEA Languages

arXiv:2608.04433 · cs.CL, cs.AI · Submitted 2026-08-05 · Read on arXiv

Qiongqiong Wang, Ai Ti Aw, Nancy F. Chen, Ying Lay Chiu, Yang Ding, Yingxu He, Ridong Jiang, Zhuohan Liu, Yanfeng Lu, Yi Ma, Muhammad Huzaifah, Nabilah Binte Md Johan, Nattadaporn Lertcheva, Pham Minh Duc, Sailor Hardik Bhupendra, Siti Umairah Binte Mohammad Salleh, Shuo Sun, Tarun Kumar Vangani, Jeremy H. M. Wong, Jinyang Wu, Longyin Zhang

cs.CL, cs.AI

Submitted: 2026-08-05

Code: https://github.com/wenet-e2e/wespeaker

License: http://creativecommons.org/licenses/by/4.0/

The gist: We present MERaLiON-GR, a speech gender recognition system that performs binary classification (female / male) on English and Southeast Asian (SEA) languages.

Terminology

Benchmark — 11× in this paper · explained in 2 episodes
Accuracy — 10× in this paper · explained in 1 episode
Generalization — 6× in this paper · explained in 14 episodes
Transformer — 6× in this paper · explained in 2 episodes
Fine-Tuning — 4× in this paper · explained in 5 episodes
Class Imbalance — 3× in this paper · explained in 3 episodes
Foundation Model — 3× in this paper · explained in 3 episodes
Low-Rank Adaptation (LoRA) — 3× in this paper · explained in 17 episodes
Language Resources and Evaluation Conference — 2× in this paper
National Speech Corpus — 2× in this paper
Representation Learning — 2× in this paper · explained in 3 episodes
Robustness — 2× in this paper · explained in 6 episodes
Weight Decay — 2× in this paper · explained in 2 episodes
Acoustic Features — 1× in this paper · explained in 1 episode
Benchmarking — 1× in this paper · explained in 4 episodes
Catastrophic Forgetting — 1× in this paper · explained in 9 episodes
Embeddings — 1× in this paper · explained in 2 episodes
Evaluation Protocol — 1× in this paper · explained in 2 episodes
Few-Shot Learning — 1× in this paper · explained in 6 episodes
Info-communications Media Development Authority — 1× in this paper
LoRA Adapters — 1× in this paper · explained in 3 episodes
Overfitting — 1× in this paper · explained in 2 episodes
Pseudo-labeling — 1× in this paper · explained in 3 episodes
Speaker Diarization — 1× in this paper · explained in 2 episodes
Verification — 1× in this paper · explained in 2 episodes

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.

MERaLiON-GR: Speech Gender Recognition Model for English and SEA Languages

Terminology

Abstract

Sources

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