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.
Damm, David; Grohganz, Harald; Kurth, Frank; Ewert, Sebastian; Clausen, Michael
Affiliations: Fraunhofer Institute for Communication, Information Processing and Ergonomics (FKIE), Wachtberg, Germany; University of Bonn, Bonn, Germany(See document for exact affiliation information.)
AES Conference: 42nd International Conference: Semantic Audio (July 2011)
Paper Number: 2-2
Publication Date: July 22, 2011
Subject: Speech Processing and Analysis
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