# High-accuracy transcription

GigaAM v2 is an automatic speech recognition (ASR) model that supports Russian speech-to-text tasks, offering both CTC and RNN-T architectures.

Turkish speech recognition model fine-tuned based on OpenAI Whisper-small

Japanese automatic speech recognition model based on Whisper, integrating speaker separation and punctuation addition functions

Korean automatic speech recognition (ASR) model fine-tuned based on OpenAI Whisper-large-v2, excelling on Korean datasets

This model is a fine-tuned version of OpenAI's Whisper Large-V2 for Hausa speech recognition tasks, trained on the Common Voice 11.0 dataset

This is a large-scale Korean automatic speech recognition model based on the Conformer-Transducer architecture, trained on the Ksponspeech dataset, suitable for Korean speech transcription tasks.

A speech-to-text (S2T) model for automatic speech recognition (ASR), based on a sequence-to-sequence transformer architecture

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

A speech recognition model based on Facebook's Wav2Vec2 architecture, pretrained on the VoxPopuli corpus and fine-tuned on Croatian data

A speech recognition model based on Facebook's Wav2Vec2 architecture, pretrained on 10K hours of unlabeled Dutch data from the VoxPopuli corpus and fine-tuned on Dutch transcription data.

This is a Punjabi speech recognition model based on the Wav2Vec2 architecture, capable of converting Punjabi speech into text.