Speech Emotion Recognition Using Machine Learning
PulseAugur coverage of Speech Emotion Recognition Using Machine Learning — every cluster mentioning Speech Emotion Recognition Using Machine Learning across labs, papers, and developer communities, ranked by signal.
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New framework enhances speech anonymization while preserving data utility
Researchers have developed a new two-stage framework for speech anonymization that aims to preserve both linguistic content and acoustic identity while maintaining data utility. This framework uses a generative speech e…
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New TTS-generated backdoor attacks exploit Speech Emotion Recognition systems
Researchers have identified a new method for backdoor attacks on Speech Emotion Recognition (SER) systems, utilizing text-to-speech (TTS) generated audio. This technique embeds subtle acoustic triggers into speech, whic…
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Whisper model adapted for Persian Speech Emotion Recognition with PCA
Researchers have explored methods to improve Speech Emotion Recognition (SER) for low-resource languages like Persian, focusing on the Whisper model. Their study proposes using Principal Component Analysis (PCA) to redu…
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HyPASE framework uses hyperbolic geometry for efficient LALM fine-tuning
Researchers have developed HyPASE, a novel framework that utilizes hyperbolic geometry for parameter-efficient fine-tuning of Large Audio-Language Models (LALMs) for Speech Emotion Recognition (SER). Unlike traditional …
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New AMRD method enables lightweight speech emotion recognition models
Researchers have developed Adaptive Multi-teacher Relational Distillation (AMRD), a novel method to create lightweight speech emotion recognition (SER) models suitable for on-device applications. AMRD addresses challeng…
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New deep learning models enhance speech emotion recognition accuracy and explainability
Researchers have developed new deep learning techniques for speech emotion recognition (SER), a field crucial for advancing human-computer interaction. One study introduces a hybrid DCRF-BiLSTM model that achieves high …
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New SpeechEQ benchmark evaluates AI emotional intelligence in voice models
Researchers have introduced SpeechEQ, a new framework designed to evaluate the emotional intelligence of speech-language models (SLMs). This framework includes a dataset of 2,265 dialogues and a multi-turn evaluation pr…
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New adapter adds test-time memory to audio LLMs for better emotion recognition
Researchers have developed a novel method called Titans-as-a-Layer (MAL) to enhance conversational speech emotion recognition. This plug-and-play adapter integrates test-time neural memory into large audio language mode…
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Audio language models improve speech emotion recognition with acoustic cues
Researchers have developed a method to improve speech emotion recognition in audio language models by incorporating explicit acoustic cues. By deriving six interpretable acoustic concept tokens from paralinguistic featu…