# TIMIT Dataset

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

This model is a fine-tuned version of facebook/wav2vec2-base, primarily used for speech recognition tasks.

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model, featuring a low Word Error Rate (WER).

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

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

This model is a speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, achieving a word error rate (WER) of 0.3384 on the evaluation set.

A speech recognition model fine-tuned based on facebook/wav2vec2-base, suitable for the TIMIT dataset

This model is a speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, focusing on English speech-to-text tasks.

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, achieving a word error rate (WER) of 0.3355 on the evaluation set.

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

A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on the TIMIT dataset with a Word Error Rate (WER) of 0.3518

This is an automatic phoneme recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-xls-r-300m model, primarily used for phoneme-level recognition of English speech.

A speech recognition model fine-tuned based on facebook/wav2vec2-base, suitable for TIMIT dataset demonstration

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

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

A speech recognition model fine-tuned based on facebook/wav2vec2-base, demonstrating excellent performance on the TIMIT dataset

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

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model

A fine-tuned speech recognition model based on facebook/wav2vec2-base, trained on the TIMIT dataset with a word error rate of 0.5855

A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on the TIMIT dataset

A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on the TIMIT dataset with a Word Error Rate (WER) of 0.4593.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, trained and evaluated on the TIMIT dataset.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.4799 on the TIMIT dataset.

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.

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model

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

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, achieving a Word Error Rate (WER) of 0.3546

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

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

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.748 on the TIMIT dataset.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.4348 on the TIMIT dataset.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, trained for 60 epochs on the TIMIT dataset with a word error rate (WER) of 1.0.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, trained for 30 epochs on the TIMIT dataset.

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, achieving a Word Error Rate (WER) of 0.6534 after 30 training epochs

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, trained on the TIMIT dataset with a Word Error Rate (WER) of 0.5426.

A speech recognition model fine-tuned on the TIMIT dataset based on the facebook/wav2vec2-base model

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

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base on the TIMIT dataset, focusing on English speech-to-text tasks.