VABench is a new multi-dimensional benchmark for evaluating synchronous audio-video generation across text-to-AV, image-to-AV, and stereo tasks.
Nisqa: A deep cnn-self-attention model for multidimensional speech quality prediction with crowdsourced datasets.arXiv preprint arXiv:2104.09494
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JASTIN is an instruction-driven audio evaluation system that achieves state-of-the-art correlation with human ratings on speech, sound, music, and out-of-domain tasks without task-specific retraining.
A Conformer-conditioned decoder-only language model generates discrete tokens via a neural audio codec to separate four music stems, reaching near state-of-the-art perceptual quality and top NISQA on vocals in MUSDB18-HQ tests.
Voice range indicates TTS model capability with VITS highest, Glow-TTS best at soft phonation, and CPPs of 7-8 dB marking natural quality while values over 10 dB sound robotic.
A structured survey of audio bandwidth extension that organizes the transition from deterministic discriminative DNNs to generative approaches including GANs, diffusion models, and flow-based methods.
citing papers explorer
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VABench: A Comprehensive Benchmark for Audio-Video Generation
VABench is a new multi-dimensional benchmark for evaluating synchronous audio-video generation across text-to-AV, image-to-AV, and stereo tasks.
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JASTIN: Aligning LLMs for Zero-Shot Audio and Speech Evaluation via Natural Language Instructions
JASTIN is an instruction-driven audio evaluation system that achieves state-of-the-art correlation with human ratings on speech, sound, music, and out-of-domain tasks without task-specific retraining.
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Discrete Token Modeling for Multi-Stem Music Source Separation with Language Models
A Conformer-conditioned decoder-only language model generates discrete tokens via a neural audio codec to separate four music stems, reaching near state-of-the-art perceptual quality and top NISQA on vocals in MUSDB18-HQ tests.
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Voice Mapping of Text-to-Speech Systems: A Metric-Based Approach for Voice Quality Assessment
Voice range indicates TTS model capability with VITS highest, Glow-TTS best at soft phonation, and CPPs of 7-8 dB marking natural quality while values over 10 dB sound robotic.
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A Survey of Advancing Audio Super-Resolution and Bandwidth Extension from Discriminative to Generative Models
A structured survey of audio bandwidth extension that organizes the transition from deterministic discriminative DNNs to generative approaches including GANs, diffusion models, and flow-based methods.