From autism to Chinese, a headset to help you with your language (Summary)
Leaning Chinese, a tonal language, is notoriously ardous. But, a wearable headset could help. The system, called SayWAT, was invented for autism people who want help with social interactions. LouAnne Boyd, the application designer, said with speech or anxiety problems - or even language learning, it could be adapted to help. When they are speaking too loudly or in a flat tone, it gives live feedback via Google Glass to the wearer. To record speech, Glass's microphone it used by it. If the user's voice does not vary in pitch and the user's voice is too loud, a volume icon and flashes is shown by it. The program could be adapted to operate on other tools. For example, a watch or smartphone watch could provide haptic response to instruction speech. Live speech reaction could help other bands too. Real-time comments when speaking a foreign language are also feasible. Giving live feedback takes a lot of computational energy, so the tool could only focus on a few facets of speech at once. But language learners could be apprised when they mess up a particular sound, such tones in Chinese.
Leaning Chinese, a tonal language, is notoriously ardous. But, a wearable headset could help. The system, called SayWAT, was invented for autism people who want help with social interactions. LouAnne Boyd, the application designer, said with speech or anxiety problems - or even language learning, it could be adapted to help. When they are speaking too loudly or in a flat tone, it gives live feedback via Google Glass to the wearer. To record speech, Glass's microphone it used by it. If the user's voice does not vary in pitch and the user's voice is too loud, a volume icon and flashes is shown by it. The program could be adapted to operate on other tools. For example, a watch or smartphone watch could provide haptic response to instruction speech. Live speech reaction could help other bands too. Real-time comments when speaking a foreign language are also feasible. Giving live feedback takes a lot of computational energy, so the tool could only focus on a few facets of speech at once. But language learners could be apprised when they mess up a particular sound, such tones in Chinese.