# Multi-scenario speech processing

Hubert-large-korean is a Korean automatic speech recognition model based on the Hubert architecture. It extracts features directly from speech waveforms through self-supervised learning and performs excellently in Korean speech processing.

An automatic speech recognition model fine-tuned on Slovenian speech datasets based on facebook/wav2vec2-xls-r-300m

Wav2Vec2 speech recognition base model pre-trained on unlabeled Spanish data from VoxPopuli

Large-scale speech pre-training model trained on the Spanish subset of the VoxPopuli corpus, suitable for Spanish speech recognition tasks

This is an automatic speech recognition (ASR) model fine-tuned for Japanese speech recognition tasks based on the facebook/wav2vec2-large-xlsr-53 model.

A speech recognition model pre-trained on unlabeled Italian data from VoxPopuli, using Facebook's Wav2Vec2 architecture

Wav2Vec2 base model pre-trained on unannotated French data from VoxPopuli, suitable for French speech recognition tasks

Large wav2vec2 model trained on 2.9K hours of French speech, supporting spontaneous speech, read speech, and broadcast speech processing

A Romanian speech recognition model fine-tuned based on facebook/wav2vec2-xls-r-300m, achieving a WER of 12.46% on the Common Voice Romanian test set

This is an automatic speech recognition (ASR) model fine-tuned on the Upper Sorbian (HSB) dataset based on Facebook's wav2vec2-xls-r-300m model.

This is an automatic speech recognition (ASR) model fine-tuned on the Odia dataset based on facebook/wav2vec2-xls-r-300m, specifically designed for Odia speech-to-text tasks.