Cross-corpus
20 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Cross-corpus
Most implemented papers
SPEAKER VGG CCT: Cross-corpus Speech Emotion Recognition with Speaker Embedding and Vision Transformers
In this paper, we start from the general idea above and develop a new learning solution for SER, which is based on Compact Convolutional Transformers (CCTs) combined with a speaker embedding.
Robust Vocal Quality Feature Embeddings for Dysphonic Voice Detection
vigor-jzhang/dysphonic-emb
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In this paper, we propose a deep learning framework for generating acoustic feature embeddings sensitive to vocal quality and robust across different corpora.
Why Can't Discourse Parsing Generalize? A Thorough Investigation of the Impact of Data Diversity
janetlauyeung/crossGENRE4RST
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To our knowledge, this study is the first to fully evaluate cross-corpus RST parsing generalizability on complete trees, examine between-genre degradation within an RST corpus, and investigate the impact of genre diversity in training data composition.
UNIDECOR: A Unified Deception Corpus for Cross-Corpus Deception Detection
Verbal deception has been studied in psychology, forensics, and computational linguistics for a variety of reasons, like understanding behaviour patterns, identifying false testimonies, and detecting deception in online communication.
Cross-corpus Readability Compatibility Assessment for English Texts
(3) Consistent outcomes across the three metrics, validating the robustness of the compatibility assessment framework.
HK-LegiCoST: Leveraging Non-Verbatim Transcripts for Speech Translation
We introduce HK-LegiCoST, a new three-way parallel corpus of Cantonese-English translations, containing 600+ hours of Cantonese audio, its standard traditional Chinese transcript, and English translation, segmented and aligned at the sentence level.
Emo-DNA: Emotion Decoupling and Alignment Learning for Cross-Corpus Speech Emotion Recognition
On one hand, our contrastive emotion decoupling achieves decoupling learning via a contrastive decoupling loss to strengthen the separability of emotion-relevant features from corpus-specific ones.
FG-Net: Facial Action Unit Detection with Generalizable Pyramidal Features
ihp-lab/fg-net
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The proposed FG-Net achieves a strong generalization ability for heatmap-based AU detection thanks to the generalizable and semantic-rich features extracted from the pre-trained generative model.
Towards Generalizable SER: Soft Labeling and Data Augmentation for Modeling Temporal Emotion Shifts in Large-Scale Multilingual Speech
spaghettisystems/emotion_whisper
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Recognizing emotions in spoken communication is crucial for advanced human-machine interaction.
Filter-based multi-task cross-corpus feature learning for speech emotion recognition
In investigating the effectiveness of its proposed method, the present research experiments on eight well-known public speech emotion corpora and compares the results with eight of the best approaches in the literature.
