In this paper, we present an automatic approach for aligning speech signals to corresponding text documents. For this sake, we propose to first use text-to-speech synthesis (TTS) to obtain a speech signal from the textual representation. Subsequently, both speech signals are transformed to sequences of audio features which are then time-aligned using a variant of greedy dynamic time-warping (DTW). The proposed approach is both efficient (with linear running time), computationally simple, and does not rely on a prior training phase as it is necessary when using HMM-based approaches. It benefits from the combination of a) a novel type of speech feature, being correlated to the phonetic progression of speech, b) a greedy left-to-right variant of DTW, and c) the TTS-based approach for creating a feature representation from the input text documents. The feasibility of the proposed method is demonstrated in several experiments.
(See document for exact affiliation information.)
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member Join the AES. If you need to check your member status, login to the Member Portal.
