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• W1971937265 abstract "Clarification dialogs can help address ASR errors in speech-to-speech translation systems and other interactive applications. We propose to use variants of Levenshtein alignment for merging an er-rorful utterance with a targeted rephrase of an error segment. ASR errors that might harm the alignment are addressed through phonetic matching, and a word embedding distance is used to account for the use of synonyms outside targeted segments. These features lead to a relative improvement of 30% of word error rate on sentences with ASR errors compared to not performing the clarification. Twice as many utterances are completely corrected compared to using basic word alignment. Furthermore, we generate a set of potential merges and train a neural network on crowd-sourced rephrases in order to select the best merger, leading to 24% more instances completely corrected. The system is deployed in the framework of the BOLT project." @default.
• W1971937265 created "2016-06-24" @default.
• W1971937265 creator A5071001941 @default.
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• W1971937265 date "2014-05-01" @default.
• W1971937265 modified "2023-10-17" @default.
• W1971937265 title "Reranked aligners for interactive transcript correction" @default.
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• W1971937265 doi "https://doi.org/10.1109/icassp.2014.6853575" @default.
• W1971937265 hasPublicationYear "2014" @default.
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