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Found 3 papers, 1 papers with code
EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models
We introduce EmphAssess, a prosodic benchmark designed to evaluate the capability of speech-to-speech models to encode and reproduce prosodic emphasis.
EXPRESSO: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis
Recent work has shown that it is possible to resynthesize high-quality speech based, not on text, but on low bitrate discrete units that have been learned in a self-supervised fashion and can therefore capture expressive aspects of speech that are hard to transcribe (prosody, voice styles, non-verbal vocalization).
Text Generation with Speech Synthesis for ASR Data Augmentation
In this work, we explore text augmentation for ASR using large-scale pre-trained neural networks, and systematically compare those to traditional text augmentation methods.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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