# Arabic speech recognition

An Arabic automatic speech recognition model fine-tuned on the QASR dataset, specifically adapted for dialectal variants

This model is a fine-tuned Arabic speech recognition model based on openai/whisper-base on the quran-ayat-speech-to-text dataset, specializing in the task of converting Quranic verses from speech to text.

An automatic speech recognition model for informal Arabic, fine-tuned based on the Whisper Tiny architecture

This model is a fine-tuned version of openai/whisper-small on Arabic datasets with diacritics, supporting Arabic speech-to-text tasks with diacritical marks.

A Quran speech recognition model fine-tuned based on OpenAI Whisper-small, specifically designed for Arabic Quran audio

Based on the transformers library, this is a fine-tuned version of openai/whisper-large-v3-turbo on the common_voice_11_0 dataset, optimized specifically for Arabic speech recognition.

This is a transformers model for Arabic alphabet speech classification, capable of recognizing and classifying the pronunciation of Arabic letters.

Arabic speech recognition model based on Whisper-large-v3, optimized for Moroccan accent

Hamsa is an Arabic speech recognition model built on the Whisper architecture, focusing on the linguistic needs of the Middle East and North Africa region.

A Whisper medium speech recognition model fine-tuned on the CommonVoice Arabic dataset, developed by the SpeechBrain team

An Arabic speech recognition model fine-tuned based on openai/whisper-medium, supporting streaming processing

This model is a fine-tuned Arabic speech recognition model based on facebook/wav2vec2-xls-r-300m on the Common Voice dataset, achieving a word error rate of 0.5078 on the evaluation set.

This model is a fine-tuned Arabic speech recognition model based on facebook/wav2vec2-large-xlsr-53 on the Common Voice dataset

An automatic speech recognition (ASR) model fine-tuned on Arabic speech datasets based on distilhubert

Arabic automatic speech recognition (ASR) model based on the data2vec architecture, fine-tuned on a 300-hour Arabic speech dataset

Arabic automatic speech recognition model based on HuBERT architecture, fine-tuned on a 300-hour Arabic speech dataset

Automatic speech recognition model trained on a large-scale Arabic speech dataset

An Arabic speech recognition model fine-tuned from facebook/wav2vec2-xls-r-300m on the Common Voice Arabic dataset

An Arabic speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

A speech recognition model fine-tuned on the Arabic Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

This model is an automatic speech recognition model fine-tuned on the Common Voice Arabic dataset based on facebook/wav2vec2-xls-r-300m.

A speech recognition model fine-tuned on the common_voice dataset based on anas/wav2vec2-large-xlsr-arabic

An Arabic automatic speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, supporting 16kHz sampling rate audio input

An Arabic speech recognition model fine-tuned on the Arabic speech corpus dataset, based on the facebook/wav2vec2-large-xlsr-53 model

An Arabic automatic speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, achieving a WER of 52% on the Common Voice Arabic dataset.

An automatic speech recognition model fine-tuned on the Arabic Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

Arabic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on Common Voice and Arabic speech corpus

This model is a transfer learning-based Arabic speech recognition system specifically designed to identify Quran recitations and locate corresponding chapters.

This model is an automatic speech recognition (ASR) model fine-tuned on the Mozilla Common Voice 8.0 Arabic dataset based on facebook/wav2vec2-xls-r-1b, supporting Arabic speech-to-text tasks.