Kirill Borodin, Vasilii Kudryavtsev, Nikita Vasiliev, Grach Mkrtchian · 2026 · arXiv
DOI: 10.48550/arXiv.2610.31470 · open-access PDF
在 LibriSpeech 和 FLEURS 上,评估识别器错过了 33-67% 的非常罕见单词,即使在人类语言中,所有三种识别器都错过了 22-42%. 检查每一个单词有两种识别器家族降低了至少一个识别器听到两到三倍的单词的明显 TTS 错误(非常罕见的 LibriSpeech 单词:从 10-13% 到 3-5%),但非常罕见
Machine translation (Meta M2M100); the English original follows.
Text-to-speech (TTS) is usually evaluated by transcribing its output with an automatic speech recognition (ASR) system, so the word error rate also counts recognizer errors. We measure these errors on human recordings of the test sentences. On LibriSpeech and FLEURS, the evaluation recognizer misses 33-67% of very rare words even in human speech, and all three recognizers miss 22-42%. Checking every word with two more recognizer families lowers the apparent TTS error on words that at least one recognizer hears two- to three-fold (very rare LibriSpeech words: from 10-13% to 3-5%), yet very rare
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