# Multi-scenario speech transcription

Persian automatic speech recognition model fine-tuned based on OpenAI Whisper-tiny, trained on the common_voice_11_0 dataset

Spanish speech recognition model fine-tuned based on Whisper-large-v3-turbo, achieving a word error rate reduction to 5.34% on the Common Voice 17.0 Spanish dataset

A speech recognition model fine-tuned on the Common Voice 17.0 Turkish dataset based on OpenAI Whisper-large-v3

A speech recognition model fine-tuned on Sinhala language based on OpenAI Whisper-small

Turkish speech recognition model fine-tuned based on OpenAI Whisper Medium, trained on the Common Voice 11.0 dataset

A Persian automatic speech recognition model fine-tuned from facebook/hubert-large-ll60k, trained using the Common Voice 7.0 Persian dataset.

This is a Swedish automatic speech recognition model fine-tuned based on the facebook/wav2vec2-large-nl-voxpopuli model, trained using the Common Voice 7.0 (sv-SE) dataset.

This model is a Turkish speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-xls-r-300m

Ukrainian automatic speech recognition model based on facebook/wav2vec2-xls-r-300m, trained on the Common Voice 10.0 dataset

This model is a Turkish speech recognition model fine-tuned on the common_voice dataset based on facebook/wav2vec2-xls-r-300m

Urdu speech recognition model based on the wav2vec2-large-xls-r-300m architecture, fine-tuned on the Common Voice dataset

A speech recognition model fine-tuned on the Common Voice 8 Urdu dataset based on facebook/wav2vec2-xls-r-300m

This model is an automatic speech recognition (ASR) model fine-tuned on the COMMON_VOICE SV-SE dataset based on facebook/wav2vec2-large-xlsr-53, supporting Swedish speech recognition.

A Wav2Vec2 base model pre-trained on a 10K unlabeled subset of the VoxPopuli corpus and fine-tuned on English transcription data, suitable for English speech recognition tasks.

A speech recognition model based on Facebook's Wav2Vec2 architecture, fine-tuned for Romanian, suitable for automatic speech recognition tasks.

A Wav2Vec2 base model pretrained on the Swedish subset of the VoxPopuli corpus, suitable for Swedish speech recognition tasks.

This is an automatic speech recognition model fine-tuned on Latvian datasets based on facebook/wav2vec2-xls-r-300m, achieving a WER of 16.98% on the Common Voice 7 test set.

XLS-R-300m speech recognition model fine-tuned on Common Voice Persian data

A speech recognition model fine-tuned on Greek language based on facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampled audio input.

Wav2Vec2 base model pretrained on unlabeled Italian data from VoxPopuli, suitable for speech recognition tasks.

A speech recognition model fine-tuned on the Common Voice Turkish dataset based on facebook/wav2vec2-xls-r-300m

Automatic speech recognition model pre-trained on the Dutch subset of the VoxPopuli corpus

This model is an automatic speech recognition model fine-tuned on Georgian language datasets based on facebook/wav2vec2-xls-r-1b

This is an automatic speech recognition model fine-tuned on Estonian datasets based on the facebook/wav2vec2-xls-r-1b model.

This is a speech recognition model fine-tuned on the Common Voice Spanish dataset based on the facebook/wav2vec2-xls-r-300m model, achieving a word error rate of 21.17% on the evaluation set.

A large-scale Portuguese automatic speech recognition (ASR) model developed by Facebook based on the Wav2Vec 2.0 architecture, supporting Portuguese speech-to-text tasks.

This is an automatic speech recognition (ASR) model fine-tuned on Ukrainian language datasets based on the facebook/wav2vec2-xls-r-300m model, achieving a 12.22% word error rate (WER) on the Common Voice Ukrainian test set.

An automatic speech recognition model fine-tuned on the Basque Common Voice dataset based on facebook/wav2vec2-xls-r-300m

This is an automatic speech recognition (ASR) model fine-tuned on the Common Voice 8.0 Turkish dataset, capable of converting Turkish speech into text.

This is an automatic speech recognition (ASR) model fine-tuned on the Turkish Common Voice 8 dataset based on Facebook's wav2vec2-xls-r-300m model.

This model is an automatic speech recognition model fine-tuned on the NBAILAB/NPSC - 48K_MP3 dataset based on KBLab/wav2vec2-large-voxrex

This is an automatic speech recognition (ASR) model based on the XLS-R architecture with 300M parameters, specifically optimized for Dutch and trained on the Common Voice 8.0 dataset.

This is an automatic speech recognition (ASR) model fine-tuned on Bulgarian speech datasets based on the facebook/wav2vec2-xls-r-300m model.

This is an automatic speech recognition (ASR) model fine-tuned on the Slovenian language (common_voice_8_0) dataset based on facebook/wav2vec2-xls-r-300m, supporting language model (LM) enhancement.

An automatic speech recognition model fine-tuned on the Assamese (Common Voice 8.0) dataset based on facebook/wav2vec2-xls-r-300m

This is an automatic speech recognition (ASR) model fine-tuned on the Dutch COMMON_VOICE dataset based on the facebook/wav2vec2-large-xlsr-53 model.

This is an automatic speech recognition model fine-tuned on Punjabi (India) dataset based on facebook/wav2vec2-xls-r-300m

This is an automatic speech recognition model fine-tuned on the Upper Sorbian (HSB) dataset based on facebook/wav2vec2-xls-r-300m, achieving a word error rate (WER) of 0.4393 on the Common Voice 8 test set.

This is a Frisian automatic speech recognition (ASR) model fine-tuned based on the wav2vec2-large-xlsr-53 model, developed by RuudVelo.