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Wavlm Bert Fusion S Emotion Russian Resd
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Wavlm Bert Fusion S Emotion Russian Resd

Developed by Aniemore
A multimodal fusion model based on WavLM and BERT, suitable for joint speech and text task processing.
Speech Recognition
Transformers
#Speech-Text Fusion#Multimodal Processing#Residual Connection Optimization
Downloads 298
Release Time : 5/2/2023

Model Overview

This model combines WavLM's speech processing capabilities with BERT's text understanding abilities, achieving cross-modal information interaction through a specific fusion strategy (k=2, s, resd=1).

Model Features

Cross-Modal Fusion
Integrates speech and text features through innovative fusion strategies.
Efficient Architecture
Combines the strengths of WavLM and BERT for efficient multimodal processing.
Parameter Optimization
Uses specific fusion parameter configurations (k=2, s, resd=1) to balance performance and efficiency.

Model Capabilities

Speech feature extraction
Text understanding
Cross-modal information fusion
Joint speech-text task processing

Use Cases

Speech-Text Alignment
Speech-to-Text Quality Assessment
Evaluates the semantic consistency between ASR system outputs and original speech.
Multimodal Sentiment Analysis
Joint Speech-Text Sentiment Recognition
Analyzes both speech content and text content for sentiment orientation.
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