# TIMIT Fine-tuning

This model is a speech recognition model fine-tuned from facebook/wav2vec2-base, achieving a word error rate (WER) of 0.5664 on the evaluation set.

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.6704 on the TIMIT dataset.

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 facebook/wav2vec2-base, for demonstration purposes

This model is an automatic speech recognition (ASR) model based on the Wav2vec 2.0 architecture, fine-tuned using a subset of the TIMIT dataset enhanced with room impulse responses (RIR).

This model is a speech recognition model fine-tuned on the TIMIT dataset, achieving a word error rate of 0.4781 and a character error rate of 0.1727 on the evaluation set.

English speech recognition model fine-tuned on the timit_asr dataset for the ascend model

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-base, with a Word Error Rate (WER) of 0.3382

A speech recognition model fine-tuned based on facebook/wav2vec2-base, trained on TIMIT and DementiaBank datasets, suitable for English speech recognition tasks.