Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace

Hesam Sagha · Jun Deng · Maryna Gavryukova · Jing Han · Björn Wolfgang Schuller

42 citations0/0 files storedIEEE International Conference on Acoustics Speech and Signal Processing

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Emotion and Mood Recognition Speech Recognition and Synthesis Domain Adaptation and Few-Shot Learning

Abstract

This paper proposes an analytical approach based on Kernel Canonical Correlation Analysis (KCCA) for domain adaptation. To generate paired instances for KCCA, we mapped source and target data onto both source and target principal components. We performed pair-wise domain adaptation between four emotional speech corpora with different languages (English, German, Italian, and Polish) to validate the approach. We compared our approach with the Shared-Hidden-Layer Auto-Encoder (SHLA) and kernel based principal components. On average, the proposed approach yields higher classification performance.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 42 citations exist upstream.

References

2005A database of German emotional speech 2010Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies 2014EMOVO Corpus: an Italian Emotional Speech Database 2008Audio-visual feature selection and reduction for emotion classification 2013On Acoustic Emotion Recognition: Compensating for Covariate Shift 2015openSMILE:)2016Enhanced semi-supervised learning for multimodal emotion recognition 2014CCA based feature selection with application to continuous depression recognition from acoustic speech features

Cited by

2019Adversarial Domain Adaption for Multi-Cultural Dimensional Emotion Recognition in Dyadic Interactions 2017Learning a Target Sample Re-Generator for Cross-Database Micro-Expression Recognition 2019Predicting Depression and Emotions in the Cross-roads of Cultures, Para-linguistics, and Non-linguistics

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.