Speech to Speech Translation

1. History

1.1. Fiction

1.1.1. Universal Translator (Star Trek)

1.1.2. TARDIS (Dr. Who)

1.1.3. 'microsofts' (Neuromance, Mona Lisa Over Drive) William Gibson

1.2. Non-Fiction

1.2.1. Interpreter (2004) by SpeechGear - mobile phone

1.2.2. NEC (2006) Japanese-English translation - mobile

1.2.3. Jibiggo -app for Mac and Androoid

1.2.4. Microsoft - Skype translator (2015

1.2.5. Google (2013) is developing a translator

2. Technologies

2.1. Natural Speech Recognition

2.2. BCI

2.3. Digital Learning

2.4. Voice Synthesis

2.5. Machine Translation

2.6. Wearbles

2.6.1. Sigmo

3. Social

3.1. Aid in widening scope of education

3.2. Help to create and strengthen personal connections between educators, students and other personnel

3.3. Create cross-cultural exchange broadening perspectives on political and socioeconomic levels

4. Uses/Context

4.1. Classroom Teacher/Student

4.2. Between Faculty

4.3. Classroom Student/Student

4.4. Acquiring Funding/Commerce

4.5. Administration/Students

4.6. Cultural Exchange

4.7. Performative/ Exploratory art

5. Negative Impacts

5.1. Possible Homogenization

5.2. Misunderstanding

5.3. Underexposure

5.4. No need to truly comprehend and learn language