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EmoBone: A Multinational Audio Dataset of Emotional Bone Conducted Speech
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/tee.22988openalex-snapshot
Multisensory speech enhancement using lower‐frequency components from bone‐conducted speech
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Recognition of Human Speech Emotion Using Variants of Mel-Frequency Cepstral Coefficients
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On measuring performance in category judgment studies of nonverbal behavior
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IEMOCAP: interactive emotional dyadic motion capture database
inferredcites →https://doi.org/10.1007/s10579-018-9427-xopenalex-snapshot
ShEMO: a large-scale validated database for Persian speech emotion detection
inferredcites →https://doi.org/10.1007/s10919-015-0209-5openalex-snapshot
Effect of Acting Experience on Emotion Expression and Recognition in Voice: Non-Actors Provide Better Stimuli than Expected
inferredcites →https://doi.org/10.1007/s12652-016-0406-zopenalex-snapshot
CHEAVD: a Chinese natural emotional audio–visual database
inferredcites →https://doi.org/10.1016/j.apacoust.2023.109337openalex-snapshot
Methods for improving word intelligibility of bone-conducted speech by using bone-conduction headphones
inferredcites →https://doi.org/10.1016/j.apergo.2010.09.004openalex-snapshot
The effect of bone conduction microphone locations on speech intelligibility and sound quality
inferredcites →https://doi.org/10.1016/j.dib.2022.108091openalex-snapshot
BanglaSER: A speech emotion recognition dataset for the Bangla language
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Speech emotion recognition using machine learning — A systematic review
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Differential selectivity for dynamic versus static information in face-selective cortical regions
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Survey on speech emotion recognition: Features, classification schemes, and databases
inferredcites →https://doi.org/10.1016/s0167-6393(02)00049-3openalex-snapshot
BabyEars: A recognition system for affective vocalizations
inferredcites →https://doi.org/10.1016/s0167-6393(03)00099-2openalex-snapshot
Speech emotion recognition using hidden Markov models
inferredcites →https://doi.org/10.1016/s0892-1997(05)80231-0openalex-snapshot
Expression of emotion in voice and music
inferredcites →https://doi.org/10.1037//0022-3514.78.1.105openalex-snapshot
Studying the dynamics of emotional expression using synthesized facial muscle movements.
inferredcites →https://doi.org/10.1080/02699939208411068openalex-snapshot
An argument for basic emotions
inferredcites →https://doi.org/10.1109/access.2018.2881096openalex-snapshot
Evaluation of an Arabic Speech Corpus of Emotions: A Perceptual and Statistical Analysis
inferredcites →https://doi.org/10.1109/access.2021.3070751openalex-snapshot
King Saud University Emotions Corpus: Construction, Analysis, Evaluation, and Comparison
inferredcites →https://doi.org/10.1109/fg.2013.6553805openalex-snapshot
Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions
inferredcites →https://doi.org/10.1109/fit.2018.00023openalex-snapshot
Cross Lingual Speech Emotion Recognition: Urdu vs. Western Languages
inferredcites →https://doi.org/10.1109/icassp.2018.8462162openalex-snapshot
CRoss-lingual and Multilingual Speech Emotion Recognition on English and French
inferredcites →https://doi.org/10.1109/icdecom.2011.5738540openalex-snapshot
IITKGP-SEHSC : Hindi Speech Corpus for Emotion Analysis
inferredcites →https://doi.org/10.1109/icsc.2020.00076openalex-snapshot
Similarity of Speech Emotion in Different Languages Revealed by a Neural Network with Attention
inferredcites →https://doi.org/10.1109/icsda.2014.7051413openalex-snapshot
Construction and analysis of Indonesian Emotional Speech Corpus
inferredcites →https://doi.org/10.1109/isspit.2006.270876openalex-snapshot
Improving Bone-Conducted Speech Quality via Neural Network
inferredcites →https://doi.org/10.1109/taffc.2014.2336244openalex-snapshot
CREMA-D: Crowd-Sourced Emotional Multimodal Actors Dataset
inferredcites →https://doi.org/10.1109/taffc.2016.2515617openalex-snapshot
MSP-IMPROV: An Acted Corpus of Dyadic Interactions to Study Emotion Perception
inferredcites →https://doi.org/10.1109/tasl.2008.2009578openalex-snapshot
Analysis of Emotionally Salient Aspects of Fundamental Frequency for Emotion Detection
inferredcites →https://doi.org/10.1111/j.0956-7976.2005.01548.xopenalex-snapshot
Deciphering the Enigmatic Face
inferredcites →https://doi.org/10.1126/science.164.3875.86openalex-snapshot
Pan-Cultural Elements in Facial Displays of Emotion
inferredcites →https://doi.org/10.1371/journal.pone.0196391openalex-snapshot
The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English
inferredcites →https://doi.org/10.1371/journal.pone.0250173openalex-snapshot
SUST Bangla Emotional Speech Corpus (SUBESCO): An audio-only emotional speech corpus for Bangla
inferredcites →https://doi.org/10.1541/ieejeiss.137.197openalex-snapshot
LP-Based Quality Improvement of Noisy Bone Conducted Speech
inferredcites →https://doi.org/10.1587/transinf.2015edl8134openalex-snapshot
Pitch Determination from Bone Conducted Speech
inferredcites →https://doi.org/10.17743/jaes.2018.0036openalex-snapshot
Speech Emotion Recognition for Performance Interaction
inferredcites →https://doi.org/10.18201/ijisae.2021473641openalex-snapshot
Punjabi Emotional Speech Database:Design, Recording and Verification
inferredcites →https://doi.org/10.21437/interspeech.2019-2753openalex-snapshot
Analysis of Deep Learning Architectures for Cross-Corpus Speech Emotion Recognition
inferredcites →https://doi.org/10.2299/jsp.27.151openalex-snapshot
Deep-Learning-Based Speech Emotion Recognition Using Synthetic Bone-Conducted Speech
inferredcites →https://doi.org/10.3389/fpsyg.2014.01532openalex-snapshot
The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults
inferredcites →https://doi.org/10.3758/brm.40.2.531openalex-snapshot
The Montreal Affective Voices: A validated set of nonverbal affect bursts for research on auditory affective processing
inferredcites →https://doi.org/10.3758/brm.42.1.74openalex-snapshot
Recognizing emotions in spoken language: A validated set of Portuguese sentences and pseudosentences for research on emotional prosody
inferredcites →https://doi.org/10.7208/chicago/9780226220802.001.0001openalex-snapshot
The Expression of the Emotions in Man and Animals
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.5281/zenodo.17384107zenodo-depositor-declared
Exploring the EmoBone Dataset with Bi-Directional LSTM for Emotion Recognition via Bone Conducted Speech
inferred← citeshttps://doi.org/10.1007/978-3-032-15346-3_49openalex-snapshot
Emotion Recognition from Bone-Conducted Speech Using Attention-Based CNN-Transformer Architecture on the EmoBone Dataset
inferred← citeshttps://doi.org/10.1016/j.specom.2025.103238openalex-snapshot
Vibravox: A dataset of french speech captured with body-conduction audio sensors
inferred← citeshttps://doi.org/10.1109/iccit64611.2024.11021978openalex-snapshot
Exploring the EmoBone Dataset with Bi-Directional LSTM and Attention for Emotion Recognition via Bone Conducted Speech
inferred← citeshttps://doi.org/10.1109/iceei68459.2025.11330456openalex-snapshot
Enhancing Robustness and Accuracy of Bone-Conducted Speech Emotion Recognition via Transformer Models
inferred← citeshttps://doi.org/10.1109/jsen.2025.3585068openalex-snapshot
Multimodal Sensor Fusion of Bone- and Air-Conducted Speech for Robust Emotion Recognition
inferred← citeshttps://doi.org/10.1109/spicscon69221.2025.11504169openalex-snapshot
Speaker Identification from Bone-Conducted Speech via Dual Attention-Transformer Model: A Study with EmoBone Dataset
inferred← citeshttps://doi.org/10.1109/sti69347.2025.11367517openalex-snapshot
Speech Emotion Recognition from Bone-Conducted Speech Using Wav2Vec2 Transformer Model
inferred← citeshttps://doi.org/10.1145/3723178.3723225openalex-snapshot
Cross-Cultural Analysis of Emotional Expression in a Multinational Speaker Dataset
inferred← citeshttps://doi.org/10.1371/journal.pone.0342953openalex-snapshot
FedEmoNet: Privacy-preserving federated learning with TCN-Transformer fusion for cross-corpus speech emotion recognition
inferred← citeshttps://doi.org/10.2139/ssrn.6890916openalex-snapshot
Beyond Emotion Labels: Multimodal AI Approaches to Affective Computing and Sentiment Modeling
inferred← citeshttps://doi.org/10.5772/intechopen.1008939openalex-snapshot
Enhancing Speech Emotion Recognition through Bone-Conducted Speech
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