# Low-resource speech processing

This model is a speech recognition model fine-tuned on the Tamil Common Voice 17.0 dataset based on OpenAI's Whisper Small, with a Word Error Rate (WER) of 43.23%.

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

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

A Whisper-large-v3 fine-tuned model for Taiwanese Hakka speech recognition, supporting multiple Hakka dialects

This is a version of thennal/whisper-medium-ml converted to the CTranslate2 model format for Malayalam speech recognition

A Thai speech recognition model fine-tuned from facebook/hubert-large-ll60k, trained on data from Common Voice 7.0

Automatic speech recognition model based on wav2vec2-large-xlsr-53, fine-tuned on the GARY109/AI_LIGHT_DANCE dataset

This is an automatic speech recognition model for Amharic, trained using wav2vec 2.0 architecture with CTC/Attention mechanism

This model is a speech recognition model fine-tuned on an unknown dataset based on facebook/wav2vec2-large-xlsr-53, supporting recognition of Arabic dialects (Arabizi).

Wav2Vec2-Large-100h-Lv60 is a large model pre-trained and fine-tuned on 100 hours of Libri-Light and Librispeech speech data, trained with self-training objectives, suitable for speech recognition tasks with 16kHz sampling rate.

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

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

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

This is a Hungarian automatic speech recognition model fine-tuned from the facebook/wav2vec2-large-xlsr-53 model, trained using the Common Voice dataset.

This model is an automatic speech recognition model fine-tuned on Vietnamese YouTube informal audio datasets, based on facebook/wav2vec2-large-xlsr-53.

A Vietnamese automatic speech recognition model fine-tuned on the PHONGDTD/VINDATAVLSP - NA dataset based on microsoft/wavlm-base-plus

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

Swahili automatic speech recognition model fine-tuned on XLSR-53 large model, supports 16kHz sampling rate audio input

A speech recognition model based on Wav2Vec 2.0 architecture, fine-tuned on the TIMIT dataset, suitable for English speech-to-text tasks

This is an automatic speech recognition model fine-tuned on Finnish based on facebook/wav2vec2-large-xlsr-53, trained using the Common Voice dataset.

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

UniSpeech is a unified speech representation learning model that combines labeled and unlabeled data for pre-training, specifically fine-tuned for Spanish phoneme recognition.

A speech recognition model based on Facebook's Wav2Vec2 architecture, pre-trained with 10K unlabeled Czech data from the VoxPopuli corpus and fine-tuned on Czech transcription data.

This is an Upper Sorbian speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, trained on data from the Common Voice dataset and online Sorbian courses.

This model is an automatic speech recognition model fine-tuned on the Common Voice 7.0 AB dataset, based on the XLS-R dummy architecture

This is a speech recognition model fine-tuned on the Yakut (Sakha) language dataset based on the facebook/wav2vec2-xls-r-300m model

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

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - LG dataset, supporting automatic speech recognition tasks for Luganda (lg).

An automatic speech recognition model fine-tuned on the TIMIT_ASR dataset based on asapp/sew-d-small-100k

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.

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on a general speech dataset, suitable for speech recognition tasks.

Pre-trained on 10K hours of unlabeled VoxPopuli corpus data and fine-tuned on Slovak transcription data

This model is a Portuguese automatic speech recognition model based on the wav2vec2 architecture, fine-tuned on the Common Voice 7 dataset, supporting 8kHz sample rate audio input.

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

This is an automatic speech recognition model fine-tuned on the Abkhazian (ab) dataset based on Facebook's wav2vec2-xls-r-300m model

This is an automatic speech recognition model fine-tuned on the COMMON_VOICE - AB dataset, based on the XLS-R Dummy architecture