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Wav2vec2 Base Lv Voxpopuli V2
A foundational speech recognition model based on Facebook's Wav2Vec2 architecture, specifically pretrained for Latvian (lv) using 13.1k hours of unlabeled data from the VoxPopuli corpus.
Downloads 29
Release Time : 3/2/2022
Model Overview
This model is a foundational speech recognition model that learns speech representations from raw audio through self-supervised learning, suitable for Latvian speech processing tasks.
Model Features
Latvian-specific
Specifically pretrained for Latvian, optimizing speech feature extraction capabilities for this language
Self-supervised learning
Uses 13.1k hours of unlabeled data for self-supervised pretraining, eliminating the need for large amounts of labeled data
16kHz audio support
Optimized for 16kHz sampled speech audio; ensure input audio sampling rate matches when using
Model Capabilities
Speech representation learning
Speech feature extraction
Foundational speech recognition model
Use Cases
Speech technology
Latvian speech recognition system
Can serve as a foundational model for further fine-tuning and development of Latvian speech recognition systems
Speech data analysis
Used for feature extraction and analysis of Latvian speech data
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