Real-time Synchronization of Live speech with Its Transcription

Most of the researches in synchronization of audio and text have been focusing on the synchronization at the level of utterance. However, to generate audio books in unstructured language like Thai from live speech, a finer level of synchronization is necessary. We propose an algorithm to synchronize live speech with its corresponding transcription in real time at syllabic unit. The proposed algorithm employs the syllable endpoint detection method and the syllable landmark detection method with bandlimited intensity as features. The experiment was conducted with LOTUS datasets and the results were compared with baseline ASR-based syllable detection. We evaluated our algorithm by measuring its error through error aberration, which is the difference of the actual number of syllables and the detected syllables for each phrase, and found average total error aberration of the proposed algorithm to outperform that of the baseline. The average total error aberrations are 11.54 and 34.21 for the proposed method and the baseline respectively. We also found the reference deviation from our method to be better than that of the baseline as well.