From the model card
Fields below are copied from the tags and counters on the HuggingFace repository alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.
- Publisher (HF namespace)
- alefiury
- Pipeline tag
- audio-classification
- Library
- Transformers
- Framework tags
- PyTorch
- Weight formats
- safetensors
- License tag
apache-2.0— read the license file in the repo before relying on it- Lineage
-
- base model facebook/wav2vec2-xls-r-300m
- fine-tune of facebook/wav2vec2-xls-r-300m
- Datasets declared
- librispeech_asr
- Downloads (HF counter at last fetch)
- 1,052,869
- Likes (HF counter at last fetch)
- 48
- Model card
- https://huggingface.co/alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech
Use cases
- Speaker gender detection in call center audio pipelines
- Demographic metadata extraction from podcast or broadcast audio
- Audio dataset stratification by predicted speaker gender
- Pre-screening step in speaker diarization workflows
- Research into fairness and bias in speech classification systems
Pros
- Fine-tuned from a 300M-parameter cross-lingual backbone, providing broad phoneme coverage
- Apache 2.0 license allows unrestricted commercial integration
- Narrow binary classification task yields fast inference with minimal compute
- HuggingFace transformers-native, requires no custom inference code
- LibriSpeech training data is well-documented, enabling reproducible evaluation
Cons
- Trained exclusively on LibriSpeech (read English speech), limiting robustness on spontaneous or accented audio
- Binary gender framing does not accommodate non-binary speaker demographics
- XLS-R-300M backbone is large relative to the simplicity of the classification task
- No published eval metrics on out-of-domain datasets in the model card
- Predictions can reflect training data biases rather than acoustic gender markers
Tags
transformerspytorchsafetensorswav2vec2audio-classificationgenerated_from_trainerdataset:librispeech_asrbase_model:facebook/wav2vec2-xls-r-300mbase_model:finetune:facebook/wav2vec2-xls-r-300mlicense:apache-2.0endpoints_compatibleregion:us