WHISTRESS extends Whisper with a token-level stress classifier trained on a new synthetic dataset, and shows zero-shot transfer to natural speech benchmarks.
EmphAssess : a Prosodic Benchmark on Assessing Emphasis Transfer in Speech-to-Speech Models
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abstract
We introduce EmphAssess, a prosodic benchmark designed to evaluate the capability of speech-to-speech models to encode and reproduce prosodic emphasis. We apply this to two tasks: speech resynthesis and speech-to-speech translation. In both cases, the benchmark evaluates the ability of the model to encode emphasis in the speech input and accurately reproduce it in the output, potentially across a change of speaker and language. As part of the evaluation pipeline, we introduce EmphaClass, a new model that classifies emphasis at the frame or word level.
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WHISTRESS: Enriching Transcriptions with Sentence Stress Detection
WHISTRESS extends Whisper with a token-level stress classifier trained on a new synthetic dataset, and shows zero-shot transfer to natural speech benchmarks.