Parrot-like speaking using optimal vector quantization
Parrot-like speaking can be considered as one of the most fundamental abilities of humans or robots. It is not a transformation of a target speech signal, but a perception-and-action process: recognizing the target speech and producing a mimic one using a voice obtained from a voice owner. This paper presents a connectionist parrot-like speaking system. Our approach employs the record-and-edit approach with an acoustic wave segment as the processing unit, and uses a vector quantizer for two purposes: to build a segment database as a natural voice of a robot, and to cluster the segment database to speed up the mimicking. The experimental parrot system works mostly well, mimicking any target speech and sounding like a voice owner.