wav2vec2_large_english_fp16.safetensors
Back

wav2vec2_large_english_fp16.safetensors
4619 1 2

Other

wav2vec2_large_english_fp16.safetensors

Model Type: Audio Encoder

  • Architecture: wav2vec 2.0

  • Language: English

  • Scale: Large

  • Precision: FP16 (Half Precision)

Main Functions:

1. Audio Feature Extraction

  • Convert raw audio waveforms into meaningful feature vectors

  • Extract phonemes, pitch, rhythm, and other information from speech

2. Speech Representation Learning

  • Understand speech content through self-supervised learning

  • Generate high-quality audio embedding vectors

Role in WanVideo Workflow:

Lip Sync

  • Analyze input English audio

  • Extract speech features to drive the digital human's lip movements

  • Ensure precise matching of lip movements and pronunciation

Time Alignment

  • Align audio features with video frames

  • Achieve audio-visual synchronization

Technical Features:

Architectural Advantages

  • Based on Transformer architecture

  • Pre-trained on large-scale unlabeled audio data

  • Exhibits excellent understanding of English speech

FP16 Advantages

  • Reduces memory usage (compared to FP32)

  • Maintains good precision

  • Faster inference speed

File Specifications:

  • Format: safetensors

  • Precision: FP16

  • Purpose: Specifically designed for English speech processing

This model is sourced from an external transfer (transfer address: GitHub - facebookresearch/fairseq ）,if the original author has objections to this transfer, you can click，
Appeal
We will, within 24 hours, edit, delete, or transfer the model to the original author according to the original author's request

user_pbs4jqfa

user_pbs4jqfa

Other

Model Information

Active
Original author：
Meta AI Research
Model Type：
Checkpoint
Basic Model：
HunyuanImage
Resource Name：
models/checkpoints/wav2vec2_large_english_fp16.safetensors
MD5：
e4c95daf355963aef43b104f8be46a92

Model Type: Audio Encoder

  • Architecture: wav2vec 2.0

  • Language: English

  • Scale: Large

  • Precision: FP16 (Half Precision)

Main Functions:

1. Audio Feature Extraction

  • Convert raw audio waveforms into meaningful feature vectors

  • Extract phonemes, pitch, rhythm, and other information from speech

2. Speech Representation Learning

  • Understand speech content through self-supervised learning

  • Generate high-quality audio embedding vectors

Role in WanVideo Workflow:

Lip Sync

  • Analyze input English audio

  • Extract speech features to drive the digital human's lip movements

  • Ensure precise matching of lip movements and pronunciation

Time Alignment

  • Align audio features with video frames

  • Achieve audio-visual synchronization

Technical Features:

Architectural Advantages

  • Based on Transformer architecture

  • Pre-trained on large-scale unlabeled audio data

  • Exhibits excellent understanding of English speech

FP16 Advantages

  • Reduces memory usage (compared to FP32)

  • Maintains good precision

  • Faster inference speed

File Specifications:

  • Format: safetensors

  • Precision: FP16

  • Purpose: Specifically designed for English speech processing

This model is sourced from an external transfer (transfer address: GitHub - facebookresearch/fairseq ）,if the original author has objections to this transfer, you can click，
Appeal
We will, within 24 hours, edit, delete, or transfer the model to the original author according to the original author's request