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Speech Technologies and Their
Applications in Mobile Learning

Dr. Agnieszka (Aga) Palalas
Prepared for M4D MOOC – October 2013
https://www.m4d-mooc.org/portal
1
Speech Technologies and Their
Applications in Mobile Learning
Outcome:
To identify how selected speech technologies can
be utilized to enhance teaching and learning using
mobile devices.

2
Speech Technologies
1. Text-to-speech (TTS)
2. Automatic speech recognition (ASR) speech-to-text

3
Speech Recognition
• Mobile audio search engine
• Voice command and control
• Dictation

• Note-taking
• Transcription of voicemails
• Voice typing

• Voice translation
• Accessibility and inclusivity
4
Text-to-Speech
• Reading back emails, messages, posts, notes
• Books read to the user (Kindle)
• Voice command and control
• Audio dictionaries

• Accessibility and inclusivity
• MALL and literacy (Roux et al, 2010)

5
Mobile-Assisted Language Learning
• Mobile-Assisted Language Learning
–
–
–
–
–

reading and speaking
dictation
communication, facilitation and feedback
pronunciation practice (speech verification)
speech analysis and language learning software
(Godwin-Jones, 2009)
– vocabulary practice (Kumar et al, 2012)

• Phonetics and phonology (Linguistics)
– speech signal processing (DSP)
– patterns recognition (AI)
6
Other Advantages
•
•
•
•

Voice-based tools - assistive technology
Individualized attention
Enforced feedback
Learner-centered: own pace, preferences,
autonomy
• Repetition and rehearsal

7
Voice Recognition Mobile Apps
Examples
• ChaCha Answers

• Google Mobile Apps
• Vlingo
• DriveSafe.ly Pro

• Dragon Downloadable Apps
• Jibbigo Voice Translation

8
Limitations
• Limited success with spontaneous, natural
foreign accented speech
• Type of mobile device
• Usability: tools
• Usability: context
• Usability: data consumption

9
Thank you!
Dr. Agnieszka Palalas
aga@epluslearning.com
LinkedIn: http://www.linkedin.com/in/apalalas
Presentations: http://www.slideshare.net/agaiza
Publications: http://athabascau.academia.edu/apalalas

References:
•

Godwin-Jones, R. (2009). Emerging technologies: Speech tools and technologies. Language Learning &
Technology, 13(3), 4-11.

•

Kumar, A., Reddy, P., Tewari, A., Agrawal, R., & Kam, M. (2012, May). Improving literacy in developing
countries using speech recognition-supported games on mobile devices. In Proceedings of the 2012
ACM annual conference on Human Factors in Computing Systems (pp. 1149-1158). ACM.

•

Roux, J., Scholtz, P., Klop, D., Povlsen, C., Jongejan, B., & Magnusdottir, A. (2010, May). Incorporating
Speech Synthesis in the Development of a Mobile Platform for e-learning. In LREC.

10

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M4D m-Learning MOOC video8: Speech technologies A-Palalas

  • 1. Speech Technologies and Their Applications in Mobile Learning Dr. Agnieszka (Aga) Palalas Prepared for M4D MOOC – October 2013 https://www.m4d-mooc.org/portal 1
  • 2. Speech Technologies and Their Applications in Mobile Learning Outcome: To identify how selected speech technologies can be utilized to enhance teaching and learning using mobile devices. 2
  • 3. Speech Technologies 1. Text-to-speech (TTS) 2. Automatic speech recognition (ASR) speech-to-text 3
  • 4. Speech Recognition • Mobile audio search engine • Voice command and control • Dictation • Note-taking • Transcription of voicemails • Voice typing • Voice translation • Accessibility and inclusivity 4
  • 5. Text-to-Speech • Reading back emails, messages, posts, notes • Books read to the user (Kindle) • Voice command and control • Audio dictionaries • Accessibility and inclusivity • MALL and literacy (Roux et al, 2010) 5
  • 6. Mobile-Assisted Language Learning • Mobile-Assisted Language Learning – – – – – reading and speaking dictation communication, facilitation and feedback pronunciation practice (speech verification) speech analysis and language learning software (Godwin-Jones, 2009) – vocabulary practice (Kumar et al, 2012) • Phonetics and phonology (Linguistics) – speech signal processing (DSP) – patterns recognition (AI) 6
  • 7. Other Advantages • • • • Voice-based tools - assistive technology Individualized attention Enforced feedback Learner-centered: own pace, preferences, autonomy • Repetition and rehearsal 7
  • 8. Voice Recognition Mobile Apps Examples • ChaCha Answers • Google Mobile Apps • Vlingo • DriveSafe.ly Pro • Dragon Downloadable Apps • Jibbigo Voice Translation 8
  • 9. Limitations • Limited success with spontaneous, natural foreign accented speech • Type of mobile device • Usability: tools • Usability: context • Usability: data consumption 9
  • 10. Thank you! Dr. Agnieszka Palalas aga@epluslearning.com LinkedIn: http://www.linkedin.com/in/apalalas Presentations: http://www.slideshare.net/agaiza Publications: http://athabascau.academia.edu/apalalas References: • Godwin-Jones, R. (2009). Emerging technologies: Speech tools and technologies. Language Learning & Technology, 13(3), 4-11. • Kumar, A., Reddy, P., Tewari, A., Agrawal, R., & Kam, M. (2012, May). Improving literacy in developing countries using speech recognition-supported games on mobile devices. In Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems (pp. 1149-1158). ACM. • Roux, J., Scholtz, P., Klop, D., Povlsen, C., Jongejan, B., & Magnusdottir, A. (2010, May). Incorporating Speech Synthesis in the Development of a Mobile Platform for e-learning. In LREC. 10