# 16kHz Sampling Rate

Automatic speech recognition model fine-tuned on the Common Voice 11.0 German dataset based on OpenAI's whisper-medium model

German medical domain speech recognition model fine-tuned based on Whisper Medium architecture, specifically optimized for Austrian Standard German pronunciation

An English text-to-speech model based on the VITS architecture, trained by Kakao Enterprise, supporting high-quality speech synthesis

This model is fine-tuned on the Common Voice, JVS, and JSUT datasets for Japanese speech recognition tasks using openai/whisper-base.

An automatic speech recognition model fine-tuned on the Common Voice 11.0 German dataset based on openai/whisper-large-v2, supporting German speech-to-text with a word error rate of 5.76

Chinese speech recognition model fine-tuned based on XLSR-53 large model, supporting 16kHz sampled audio input

A Chinese speech recognition model fine-tuned based on microsoft/wavlm-large, supporting Simplified Chinese, trained using the Common Voice 7.0 (zh-CN) dataset.

An automatic speech recognition model fine-tuned using the Common Voice 7.0 French dataset, based on the facebook/wav2vec2-xls-r-300m model

A Japanese automatic speech recognition model fine-tuned using the training set of Common Voice 7.0 (Japanese version), based on the facebook/wav2vec2-large-it-voxpopuli model.

A Japanese automatic speech recognition model fine-tuned based on the microsoft/unispeech-sat-large model, trained using the Common Voice 7.0 Japanese dataset.

A Japanese automatic speech recognition model fine-tuned based on microsoft/wavlm-large, trained using the Common Voice 7.0 Japanese dataset

A Japanese automatic speech recognition model fine-tuned using the Common Voice 7.0 (Japanese) dataset, based on the microsoft/unispeech-large-1500h-cv model

Japanese automatic speech recognition model fine-tuned based on facebook/wav2vec2-large-xlsr-53, trained using Common Voice 7.0 Japanese dataset

An English speech recognition model fine-tuned based on Microsoft's UniSpeech-SAT-Large model, supporting 16kHz sampled audio input.

Wav2Vec2 large speech recognition model fine-tuned on the TEDLIUM corpus, supporting English speech-to-text conversion

A Chinese speech recognition model fine-tuned on the AISHELL-1 dataset based on facebook/wav2vec2-large-xlsr-53, supporting Chinese speech recognition tasks.

An automatic speech recognition (ASR) model fine-tuned on the Persian Common Voice dataset based on Facebook's wav2vec2-large-xlsr-53 model

An automatic speech recognition model fine-tuned on the Common Voice German dataset based on facebook/wav2vec2-large-xlsr-53, achieving a test WER of 15.80%.

A speech recognition model fine-tuned on the timit_asr dataset based on facebook/wav2vec2-base, supporting 16kHz sampled audio input

A fine-tuned Egyptian Arabic automatic speech recognition model based on facebook/wav2vec2-large-xlsr-53, trained using the arabicspeech.org MGB-3 dataset.

This is a German automatic speech recognition model based on the XLS-R 1B architecture, fine-tuned on multiple German speech datasets including Common Voice 8.0

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

A speech recognition model fine-tuned on the German Common Voice dataset based on facebook/wav2vec2-large-xlsr-53, with a word error rate of 29.35%

A speech recognition model fine-tuned on the TIMIT dataset based on facebook/wav2vec2-large-lv60, supporting 16kHz sampled speech input.

Based on Facebook's wav2vec2-xls-r-300m model, fine-tuned on the Common Voice German dataset, supporting German speech recognition with preserved text case information.

A Japanese automatic speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53 using the Common Voice and JSUT datasets.

This is an audio source separation model based on the SepFormer architecture, trained on the WHAMR! dataset, suitable for separating audio signals at a 16kHz sampling rate.

A Chinese (zh-CN) speech recognition model fine-tuned on the Common Voice dataset based on facebook/wav2vec2-large-xlsr-53

An English fine-tuned speech recognition model based on facebook/wav2vec2-large, using the Common Voice dataset, supporting 16kHz sampled audio input.

A speech recognition model fine-tuned on Cantonese (using the Common Voice dataset) based on facebook/wav2vec2-large-xlsr-53

This is a ConvTasNet model trained based on the Asteroid framework, specifically designed for audio separation tasks, trained on the sep_clean task of the Libri2Mix dataset.

Japanese speech recognition model fine-tuned from facebook/wav2vec2-large-xlsr-53, supports 16kHz sampling rate input