请注意,该模型应该在下游任务上进行微调,例如自动语音识别。 jonatasgrosman/wav2vec2-large-xlsr-53-english是基于 Wav2Vec2 XLSR 的流行的英语微调 CTC 模型,其他语言的模型也已得到训练。 如果您想无论如何使用模型的输出(仅从音频获取特征向量),请使用 aWav2Vec2FeatureExtractor代替Wav2Vec2Processor,并Wav...
Wav2Vec2-Large-XLSR-53 The base model pretrained and fine-tuned on 960 hours of Librispeech on 16kHz sampled speech audio. When using the model make sure that your speech input is also sampled at 16Khz. More Info Meta AI Research post:Wav2vec 2.0: Learning the structure of speech from...
The resulting model of this notebook has been saved to patrickvonplaten/wav2vec2-large-xlsr-turkish-demoAs a final check, let's load the model and verify that it indeed has learned to transcribe Turkish speech.Let's first load the pretrained checkpoint.model = Wav2Vec2ForCTC...
Wav2Vec2-Large-XLSR-Persian-ASR / README.mdLatest commit HistoryHistory File metadata and controls Preview Code Blame 3 lines (2 loc) · 170 Bytes Raw Wav2Vec2-Large-XLSR-Persian-ASR visit https://huggingface.co/lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMO...
XLSR-53 Large 56k 53 MLS, CommonVoice, BABEL download The XLSR model uses the following datasets for multilingual pretraining: MLS: Multilingual LibriSpeech (8 languages, 50.7k hours): Dutch, English, French, German, Italian, Polish, Portuguese, Spanish CommonVoice (36 languages, 3.6k hours)...
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Upon its release, two model sizes were available: the BASE model with 95 million parameters and the LARGE model with 317 million parameters.XLS-R, on the other hand, was pretrained on multilingual speech audio from 5 datasets:VoxPopuli: A total of ~372,000 hours of speech audio across...
Repository files navigation README GPL-3.0 license Wav2Vec2-Large-XLSR-Persian-ASR visit https://huggingface.co/lnxdx/Wav2Vec2-Large-XLSR-Persian-ShEMOAbout No description, website, or topics provided. Resources Readme License GPL-3.0 license Activity Stars 1 star Watchers 1 watching ...
Great, you can see the just created repository under `https://huggingface.co/<your-username>/wav2vec2-large-xlsr-turkish-demo-colab` ### Create XLSR-Wav2Vec2 Feature Extractor @@ -332,75 +370,59 @@ from transformers import Wav2Vec2Processor processor = Wav2Vec2Processor(feature_extract...
Train a wav2vec 2.0 large model: Fine-tune a pre-trained model with CTC: Evaluating a CTC model: Use wav2vec 2.0 with 🤗Transformers: wav2vec Pre-trained models Example usage: Training a new model with the CLI tools Prepare training data manifest: ...