mlsanityData to 7 Oct 2026

Speech Sentiment Analysis via Pre-trained Features from End-to-end ASR Models

arXiv 1911.09762 ↗First posted 21 Nov 2019cs.CL cs.LG eess.AScited by 21

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Abstract (arXiv)

In this paper, we propose to use pre-trained features from end-to-end ASR models to solve speech sentiment analysis as a down-stream task. We show that end-to-end ASR features, which integrate both acoustic and text information from speech, achieve promising results. We use RNN with self-attention as the sentiment classifier, which also provides an easy visualization through attention weights to help interpret model predictions. We use well benchmarked IEMOCAP dataset and a new large-scale speech sentiment dataset SWBD-sentiment for evaluation. Our approach improves the-state-of-the-art accuracy on IEMOCAP from 66.6% to 71.7%, and achieves an accuracy of 70.10% on SWBD-sentiment with more than 49,500 utterances.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Nov 2019.

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Citing papers per year: 2021: 6; 2022: 3; 2023: 6; 2024: 1; 2025: 5.

21 papers.

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  1. 2021SLUE: New Benchmark Tasks for Spoken Language Understanding Evaluation on Natural Speechcited by 70
  2. 2022Speech Emotion Recognition using Self-Supervised Featurescited by 52
  3. 2023Paralinguistics-Enhanced Large Language Modeling of Spoken Dialoguecited by 25
  4. 2021DeToxy: A Large-Scale Multimodal Dataset for Toxicity Classification in Spoken Utterancescited by 13
  5. 2021Leveraging Pre-trained Language Model for Speech Sentiment Analysiscited by 8
  6. 2022MMER: Multimodal Multi-task Learning for Speech Emotion Recognitioncited by 7
  7. 2021The Role of Phonetic Units in Speech Emotion Recognitioncited by 6
  8. 2024MFHCA: Enhancing Speech Emotion Recognition Via Multi-Spatial Fusion and Hierarchical Cooperative Attentioncited by 6
  9. 2023Speech Emotion Recognition with Distilled Prosodic and Linguistic Affect Representationscited by 4
  10. 2023A Comprehensive Study on the Effectiveness of ASR Representations for Noise-Robust Speech Emotion Recognitioncited by 4
  11. 2023Lego-Features: Exporting modular encoder features for streaming and deliberation ASRcited by 3
  12. 2022CTA-RNN: Channel and Temporal-wise Attention RNN Leveraging Pre-trained ASR Embeddings for Speech Emotion Recognitioncited by 2
9 more
  1. 2025Spoken Language Understanding on Unseen Tasks With In-Context Learningcited by 2
  2. 2021Beyond Isolated Utterances: Conversational Emotion Recognitioncited by 1
  3. 2025Switchboard-Affect: Emotion Perception Labels from Conversational Speechcited by 1
  4. 2021Dialog speech sentiment classification for imbalanced datasetscited by 0
  5. 2023e-Inu: Simulating A Quadruped Robot With Emotional Sentiencecited by 0
  6. 2023"We care": Improving Code Mixed Speech Emotion Recognition in Customer-Care Conversationscited by 0
  7. 2025UniSLU: Unified Spoken Language Understanding from Heterogeneous Cross-Task Datasetscited by 0
  8. 2025Enhancing Speech Emotion Recognition Leveraging Aligning Timestamps of ASR Transcripts and Speaker Diarizationcited by 0
  9. 2025Speech Emotion Recognition via Entropy-Aware Score Selectioncited by 0