#acoustic-models News & Analysis

3 articles tagged with #acoustic-models. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

3 articles

AINeutralarXiv – CS AI · Jun 256/10

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From Sounds to Scenes: A Benchmark for Evaluating Context-Aware Auditory Scene Understanding in Large Audio Language Models

Researchers introduce CASU, a new benchmark for evaluating Large Audio Language Models' ability to understand complex auditory scenes by integrating multiple acoustic layers—speech, sound events, and background environments—rather than processing them in isolation. The benchmark reveals that current LALMs struggle with holistic scene comprehension and require integration across all audio layers for effective real-world audio understanding.

AINeutralarXiv – CS AI · Jun 235/10

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How Well Do Self-Supervised Speech Models Encode Age and Gender in Children's Speech? A Layer-Wise Analysis Across Multiple Architectures

Researchers conducted a comprehensive layer-wise analysis of how four major self-supervised learning (SSL) speech models encode age and gender information in children's speech. The study reveals that age and gender cues are unevenly distributed across model layers, with early-to-mid layers capturing the strongest paralinguistic signals, and demonstrates reliable classification accuracy even from 1-3 second audio segments.

AINeutralarXiv – CS AI · Jun 196/10

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Systematic Study of Dysarthric Speech Recognition: Spectral Features and Acoustic Models

Researchers have achieved significant improvements in dysarthric speech recognition by systematically combining acoustic features with the Factorized Time Delay Neural Network (F-TDNN) model, demonstrating 4.65% relative improvement in word recognition and 4.63% in sentence recognition. The study identifies pitch features as particularly effective for handling the acoustic variability characteristic of impaired speech, advancing accessibility technology for individuals with speech disorders.