Methods › Computer Vision › Multi-Modal Methods › CTAL

CTAL

2 papers tagged archive 2025-07-28

Introduced by Hang Li et al. in CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

CTAL is a pre-training framework for strong audio-and-language representations with a Transformer, which aims to learn the intra-modality and inter-modalities connections between audio and language through two proxy tasks on a large amount of audio- and-language pairs: masked language modeling and masked cross-modal acoustic modeling. The pre-trained model is a Transformer for Audio and Language, i.e., CTAL, which consists of two modules, a language stream encoding module which adapts word as input element, and a text-referred audio stream encoder module which accepts both frame-level Mel-spectrograms and token-level output embeddings from the language stream

PaperSource

Papers archive 2025-07-28

2 shown of 2, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

7 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Decoder1
Emotion Classification1
Language Modeling1
Language Modelling1
Masked Language Modeling1
Sentiment Analysis1
Speaker Verification1

Usage over time archive 2025-07-28

Papers per year tagged with CTAL: 2021 to 2024, peak 1 1 0 2021: 1 paper 2021 2022: 0 papers 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (2 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Multi-Modal MethodsGenerative Audio Models

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