Papers Cross-corpus
“Cross-corpus” 태그가 달린 논문 81편 · 필터 해제
Tracking Articulatory Dynamics in Speech with a Fixed-Weight BiLSTM-CNN Architecture
Speech production is a complex sequential process which involve the coordination of various articulatory features. Among them tongue being a highly versatile active articulator responsible for shaping airflow to produce …
Cross-corpusIs It Still Fair? Investigating Gender Fairness in Cross-Corpus Speech Emotion Recognition
Speech emotion recognition (SER) is a vital component in various everyday applications. Cross-corpus SER models are increasingly recognized for their ability to generalize performance. However, concerns arise regarding f…
Cross-corpusEmotion RecognitionFairnessSpeech Emotion Recognition+1Mouth Articulation-Based Anchoring for Improved Cross-Corpus Speech Emotion Recognition
Cross-corpus speech emotion recognition (SER) plays a vital role in numerous practical applications. Traditional approaches to cross-corpus emotion transfer often concentrate on adapting acoustic features to align with d…
Cross-corpusEmotion RecognitionSpeech Emotion RecognitionTransfer LearningBidirectional Topic Matching: Quantifying Thematic Overlap Between Corpora Through Topic Modelling
This study introduces Bidirectional Topic Matching (BTM), a novel method for cross-corpus topic modeling that quantifies thematic overlap and divergence between corpora. BTM is a flexible framework that can incorporate v…
ArticlesCross-corpusTopic ModelsCross-Task Inconsistency Based Active Learning (CTIAL) for Emotion Recognition
Emotion recognition is a critical component of affective computing. Training accurate machine learning models for emotion recognition typically requires a large amount of labeled data. Due to the subtleness and complexit…
Active LearningCross-corpusEmotion ClassificationEmotion RecognitionA Cross-Corpus Speech Emotion Recognition Method Based on Supervised Contrastive Learning
Research on Speech Emotion Recognition (SER) often faces challenges such as the lack of large-scale public datasets and limited generalization capability when dealing with data from different distributions. To solve this…
Contrastive LearningCross-corpusEmotion RecognitionSpeech Emotion RecognitionVocalTweets: Investigating Social Media Offensive Language Among Nigerian Musicians
Musicians frequently use social media to express their opinions, but they often convey different messages in their music compared to their posts online. Some utilize these platforms to abuse their colleagues, while other…
Binary ClassificationCross-corpusAfriHuBERT: A self-supervised speech representation model for African languages
In this work, we present AfriHuBERT, an extension of mHuBERT-147, a compact self-supervised learning (SSL) model pretrained on 147 languages. While mHuBERT-147 covered 16 African languages, we expand this to 1,226 throug…
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)Cross-corpusLanguage Identification+4The Whole Is Bigger Than the Sum of Its Parts: Modeling Individual Annotators to Capture Emotional Variability
Emotion expression and perception are nuanced, complex, and highly subjective processes. When multiple annotators label emotional data, the resulting labels contain high variability. Most speech emotion recognition tasks…
Cross-corpusEmotion RecognitionSpeech Emotion RecognitionEEG-SCMM: Soft Contrastive Masked Modeling for Cross-Corpus EEG-Based Emotion Recognition
Emotion recognition using electroencephalography (EEG) signals has garnered widespread attention in recent years. However, existing studies have struggled to develop a sufficiently generalized model suitable for differen…
Contrastive LearningCross-corpusEEGEmotion Recognition+1Prompting Whisper for QA-driven Zero-shot End-to-end Spoken Language Understanding
Zero-shot spoken language understanding (SLU) enables systems to comprehend user utterances in new domains without prior exposure to training data. Recent studies often rely on large language models (LLMs), leading to ex…
Cross-corpusDecoderQuestion Answeringslot-filling+2EmoBox: Multilingual Multi-corpus Speech Emotion Recognition Toolkit and Benchmark
Speech emotion recognition (SER) is an important part of human-computer interaction, receiving extensive attention from both industry and academia. However, the current research field of SER has long suffered from the fo…
Cross-corpusEmotion RecognitionSpeech Emotion RecognitionDB3V: A Dialect Dominated Dataset of Bird Vocalisation for Cross-corpus Bird Species Recognition
In ornithology, bird species are known to have variedit's widely acknowledged that bird species display diverse dialects in their calls across different regions. Consequently, computational methods to identify bird speci…
BenchmarkingCross-corpusJoint Contrastive Learning with Feature Alignment for Cross-Corpus EEG-based Emotion Recognition
The integration of human emotions into multimedia applications shows great potential for enriching user experiences and enhancing engagement across various digital platforms. Unlike traditional methods such as questionna…
Contrastive LearningCross-corpusEEGEmotion RecognitionAudio-Visual Compound Expression Recognition Method based on Late Modality Fusion and Rule-based Decision
This paper presents the results of the SUN team for the Compound Expressions Recognition Challenge of the 6th ABAW Competition. We propose a novel audio-visual method for compound expression recognition. Our method relie…
Cross-corpusEmotion Recognitionzero-shot-classificationZero-Shot LearningFilter-based multi-task cross-corpus feature learning for speech emotion recognition
Speech emotion recognition is a highly active field of research in human–machine interaction. A primary challenge faced by researchers in this area is how to tackle the problem of changing data distribution. In the last…
Cross-corpusEmotion Recognitionfeature selectionMulti-Task Learning+1HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools
With the exponential growth of the life science literature, biomedical text mining (BTM) has become an essential technology for accelerating the extraction of insights from publications. Identifying named entities (e.g.,…
Cross-corpusnamed-entity-recognitionNamed Entity RecognitionParameter Efficient Finetuning for Speech Emotion Recognition and Domain Adaptation
Foundation models have shown superior performance for speech emotion recognition (SER). However, given the limited data in emotion corpora, finetuning all parameters of large pre-trained models for SER can be both resour…
Cross-corpusDomain AdaptationEmotion RecognitionSpeech Emotion RecognitionInvestigating the Generalizability of Physiological Characteristics of Anxiety
Recent works have demonstrated the effectiveness of machine learning (ML) techniques in detecting anxiety and stress using physiological signals, but it is unclear whether ML models are learning physiological features sp…
Cross-corpusInformation Type Classification with Contrastive Task-Specialized Sentence Encoders
User-generated information content has become an important information source in crisis situations. However, classification models suffer from noise and event-related biases which still poses a challenging task and requi…
ClassificationCross-corpusSentence