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pro vyhledávání: '"Marco, Divette"'
We investigate which prosodic features matter most in conveying prosodic functions. We use the problem of predicting human perceptions of pragmatic similarity among utterance pairs to evaluate the utility of prosodic features of different types. We f
Externí odkaz:
http://arxiv.org/abs/2408.13240
Autor:
Ward, Nigel G., Marco, Divette
Automatic measures of similarity between utterances are invaluable for training speech synthesizers, evaluating machine translation, and assessing learner productions. While there exist measures for semantic similarity and prosodic similarity, there
Externí odkaz:
http://arxiv.org/abs/2403.14808
To support machine learning of cross-language prosodic mappings and other ways to improve speech-to-speech translation, we present a protocol for collecting closely matched pairs of utterances across languages, a description of the resulting data col
Externí odkaz:
http://arxiv.org/abs/2211.11584