# High-precision transcription

A Whisper model released by the National Library of Sweden, optimized for Swedish speech recognition, significantly reducing the error rate compared to the original OpenAI version.

A Whisper model trained on over 50,000 hours of Swedish speech data released by the National Library of Sweden, excelling in Swedish speech recognition tasks

Russian automatic speech recognition (ASR) model optimized based on OpenAI Whisper Large V3 Turbo, fine-tuned using the Mozilla Common Voice 17 Russian dataset

This model is an automatic speech recognition model fine-tuned on the Burmese speech dataset based on openai/whisper-large-v3, specifically designed for Burmese speech transcription.

A fine-tuned Uzbek speech recognition model based on Oyqiz/uzbek_stt, specifically optimized for legal and military domain data

Fine-tuned based on Facebook's wav2vec2-base model, specifically optimized for Korean speech recognition, and can accurately transcribe Korean speech into text.

This is a Russian speech recognition model based on Whisper Large V3, specifically optimized for Russian speech.

A speech recognition model fine-tuned on Dutch datasets based on OpenAI Whisper Large V2, with a word error rate of 10.14%

An automatic speech recognition model developed by the National Library of Norway, based on the Whisper architecture, supporting speech transcription and translation of Norwegian and English.

Whisper large-v3 is a large-scale multilingual automatic speech recognition (ASR) model developed by OpenAI, supporting speech-to-text tasks in multiple languages.

This is the CTranslate2 converted version of OpenAI Whisper large-v2 model for efficient speech recognition

An automatic speech recognition (ASR) model fine-tuned on Japanese speech datasets based on OpenAI Whisper-large-v2

An automatic speech recognition model fine-tuned on Polish datasets based on Whisper Large v2, supporting Polish speech-to-text tasks.

A speech recognition model fine-tuned on Indonesian datasets based on openai/whisper-medium, significantly improving the accuracy of Indonesian recognition.

Icefall is an automatic speech recognition (ASR) toolkit based on the k2 framework, focusing on efficient and flexible speech recognition model training and inference.

Russian speech recognition model based on wav2vec2 architecture, with recognition results that can be post-processed by a companion text correction network

This is an automatic speech recognition model fine-tuned on the Swedish Common Voice dataset based on KBLab/wav2vec2-large-voxrex

A Korean automatic speech recognition model based on the wav2vec2-xlsr architecture, specifically optimized for elderly Korean speech

This is an automatic speech recognition model for Hindi, performing well on datasets like Common Voice.