# Multi-scenario Speech Transcription

Whisper-medium model fine-tuned on approximately 800 hours of diverse Estonian data, suitable for general speech recognition scenarios

This is a speech recognition model fine-tuned on the Serbian Common Voice 11.0 dataset based on OpenAI Whisper Large-V2, achieving a word error rate of 10.76%.

This model is a speech recognition model fine-tuned on the common_voice_9_0 dataset based on facebook/wav2vec2-xls-r-300m, supporting Portuguese speech-to-text tasks.

This model is a Russian speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-xls-r-300m, achieving a word error rate of 0.468 on the evaluation set.

A Dutch automatic speech recognition (ASR) model developed by Facebook based on the Wav2Vec 2.0 architecture, fine-tuned using the XLSR-53 multilingual pretrained model

A Bulgarian speech recognition model fine-tuned on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - BG dataset based on facebook/wav2vec2-xls-r-300m