Utterances by L2 speakers can be unintelligible due to mispronunciation and improper prosody. In computer-aided language learning systems, textual feedback is often provided using a speech recognition engine. However, an ideal form of feedback for L2 speakers should be so fine-grained that it enables them to detect and diagnose unintelligible parts of L2 speakers' utterances. Inspired by language teachers who correct students' pronunciation through a voice-to-voice process, this pilot study utilizes a unique semi-parallel dataset composed of non-native speakers' (L2) reading aloud, shadowing of native speakers (L1) and their script-shadowing utterances. We explore the technical possibility of replicating the process of an L1 speaker's shadowing L2 speech using Voice Conversion techniques, to create a virtual shadower system. Experimental results demonstrate the feasibility of the VC system in simulating L1's shadowing behavior. The output of the virtual shadower system shows a reasonable similarity to the real L1 shadowing utterances in both linguistic and acoustic aspects.

A cyranoid is a person who speaks the words of another person. With the help of a hidden earpiece, a'source' whispers words into the ear of a'shadower', who repeats them. In research published last year, British psychologists Kevin Corti and Alex Gillespie showed that cyranoids are hard to spot: if you were speaking to one, you probably wouldn't know it, even if the source was an adult and the shadower a child, or vice versa. Now Corti and Gillespie are back with an even more striking experiment. In their new research, published in Frontiers in Psychology, they set up a scenario in which a human's words were controlled by a computer chat-bot.