# TIMIT dataset

English phoneme recognition model fine-tuned from facebook/wav2vec2-large-lv60, achieving a phoneme error rate of 10.53% on the TIMIT dataset

This model is a speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base and trained in the Google Colab environment.

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model, suitable for English speech-to-text tasks.

This model is a speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, with a word error rate (WER) of 0.2574 on the evaluation set.

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model, primarily used for English speech-to-text tasks.

This model is an automatic speech recognition model fine-tuned on the TIMIT_ASR - NA dataset, based on patrickvonplaten/wav2vec2-base-repro-960h-libri-85k-steps.

An automatic speech recognition (ASR) model fine-tuned on the TIMIT_ASR dataset based on microsoft/unispeech-sat-base-plus

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

This model is an automatic speech recognition model fine-tuned from asapp/sew-d-small-100k on the TIMIT_ASR - NA dataset, achieving a word error rate of 0.8061 on the evaluation set.

A speech recognition model fine-tuned on the timit_asr dataset based on facebook/wav2vec2-large-lv60