Attention2Probability

Attention2Probability is a lightweight intervention scheme for speech terminology. The core approach uses a cross-attention mechanism to retrieve terms likely to appear in audio, which are then added to an LLM prompt for term intervention. The dataset, created by ByteDance, was last updated on Hugging Face on August 27, 2025.

Use Cases

• Improving automatic speech recognition (ASR) accuracy for domain-specific terminology based on the described attention-driven intervention scheme.
• Enhancing large language model (LLM) prompts for speech-to-text tasks based on the described method of term retrieval from audio.
• Benchmarking lightweight intervention techniques for speech terminology recognition.

Strengths

• Implements a specific, described methodology (cross-attention mechanism for term retrieval).
• Authored by ByteDance, a known organization in the tech industry.
• Last update timestamp is explicitly provided (2025-08-27 02:11:06).

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count, file formats, and audio data availability are unknown, which may limit suitability assessment.

Provenance

Source

ByteDance

Collection Method

Likely involves processing audio and text data for the described attention-driven terminology intervention scheme.

Freshness

Last updated 2025-08-27 02:11:06; freshness should be verified.