Intelligibility Assessment of the De-Identified Speech Obtained Using Phoneme Recognition and Speech Synthesis Systems

Abstract

The paper presents and evaluates a speaker de-identification technique using speech recognition and two speech synthesis techniques. The phoneme recognition system is built using HMM-based acoustical models of context-dependent diphone speech units, and two different speech synthesis systems (diphone TD-PSOLA-based and HMM-based) are employed for re-synthesizing the recognized sequences of speech units. Since the acoustical models of the two speech synthesis systems are assumed to be completely independent of the input speaker’s voice, the highest level of input speaker de-identification is ensured. The proposed de-identification system is considered to be language dependent, but is, however, vocabulary and speaker independent since it is based mainly on acoustical modelling of the selected diphone speech units. Due to the relatively simple computing methods, the whole de-identification procedure runs in real-time.