# wav2vec2 Architecture

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset, primarily used for speech recognition tasks, achieving an accuracy of 84.55% on the evaluation set.

Gender recognition model fine-tuned on Librispeech-clean-100 dataset, achieving an F1 score of 0.9993 on the test set

A voice anti-spoofing detection model fine-tuned on the ASVspoof2019 dataset based on facebook/wav2vec2-base

A speech recognition model fine-tuned based on facebook/wav2vec2-base, achieving an accuracy of 87.27% on the evaluation set.

A Swedish automatic speech recognition model fine-tuned from facebook/wav2vec2-large-robust, supporting 16kHz sampling rate audio input.

A speech recognition model fine-tuned based on facebook/wav2vec2-base-960h

A speech recognition model fine-tuned based on facebook/wav2vec2-base-960h, achieving a word error rate of 1.0 on the evaluation set

This model is a fine-tuned speech recognition model based on facebook/wav2vec2-base, achieving a word error rate of 0.4949 on the evaluation set.

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

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

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

A speech recognition model fine-tuned on an empty dataset based on facebook/wav2vec2-base, using random high-pass filter technology to process training data