wav2vec2-base-de-voxpopuli-v2 Open-Source German Speech Model - Empowering German Speech Recognition and Processing

Wav2vec2 Base De Voxpopuli V2

Developed by facebook

A German speech pretrained model based on Facebook's Wav2Vec2 architecture, pretrained using 23.2k unlabeled German data from the VoxPopuli corpus.

Speech Recognition

Transformers

German#German speech recognition #Unsupervised pretraining #16kHz audio processing

Downloads 44

Release Time : 3/2/2022

Model Overview

This model is a foundational speech processing model focused on German speech recognition tasks, extracting features from raw audio through self-supervised learning.

Model Features

German-specific pretraining

Pretrained specifically on German speech data, optimizing feature extraction capabilities for German speech.

Self-supervised learning

Utilizes Wav2Vec2's self-supervised learning approach to learn effective representations from large amounts of unlabeled speech data.

16kHz audio support

The model is pretrained on 16kHz sampled speech audio; ensure input audio matches this sampling rate during use.

Model Capabilities

German speech feature extraction

Speech representation learning

Use Cases

Speech processing

German speech recognition system

Build a German automatic speech recognition system by fine-tuning this model

Additional labeled data is required for fine-tuning to achieve optimal performance

Speech feature extractor

Use as a feature extractor for downstream speech tasks

🚀 Wav2Vec2-base-VoxPopuli-V2

This project presents a pre - trained base model derived from Facebook's Wav2Vec2. It is specifically pre - trained in German on 23.2k unlabeled data from the VoxPopuli corpus, offering a solid foundation for audio - related tasks, especially in the German language.

🚀 Quick Start

The model is pre - trained on 16kHz sampled speech audio. When using the model, ensure that your speech input is also sampled at 16kHz.

✨ Features

Language - Specific Pretraining: The model is pre - trained only in German, making it well - suited for German speech - related tasks.
Audio - Only Pretraining: It was pre - trained on audio alone, without a tokenizer initially.

📚 Documentation

Model Details

This model is a base model of Facebook's Wav2Vec2, pre - trained on the VoxPopuli corpus. The pre - training is conducted on 23.2k unlabeled data.

Fine - Tuning

This model does not have a tokenizer as it was pre - trained on audio alone. To use this model for speech recognition, a tokenizer should be created, and the model should be fine - tuned on labeled text data in German. Check out [this blog](https://huggingface.co/blog/fine - tune - xlsr - wav2vec2) for a more in - detail explanation of how to fine - tune the model.

Paper

Authors

The authors are Changhan Wang, Morgane Riviere, Ann Lee, Anne Wu, Chaitanya Talnikar, Daniel Haziza, Mary Williamson, Juan Pino, Emmanuel Dupoux from Facebook AI.

Additional Information

See the official website for more information, here.

📄 License

The model is released under the cc - by - nc - 4.0 license.

📦 Information Table

Property	Details
Model Type	Wav2Vec2 base model pre - trained on German audio data
Training Data	23.2k unlabeled data from the VoxPopuli corpus
License	cc - by - nc - 4.0

📝 Important Notes

⚠️ Important Note

This model does not have a tokenizer as it was pre - trained on audio alone. To use it for speech recognition, a tokenizer should be created and the model should be fine - tuned on labeled text data in German.

💡 Usage Tip

When using the model, make sure that your speech input is sampled at 16kHz, as the model is pre - trained on 16kHz sampled speech audio.

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