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DictaLearn was built intuitively by a developer solving a personal frustration with pronunciation practice. While not originally designed from academic research, the platform's approach aligns with established principles in learning science and speech technology.
Sources: MDN SpeechRecognition, DictaLearn Methodology
DictaLearn encourages regular, short practice sessions (15 minutes daily) rather than infrequent long sessions. This approach aligns with research showing that distributing practice over time leads to more durable learning than massed practice.
📚 Supporting research: Cepeda, N. J., et al. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380. [Link]
The platform adjusts content difficulty based on your performance. When you consistently score well, content becomes more challenging; when you struggle, it provides additional practice at your current level. This adaptive approach aligns with mastery learning principles that emphasize proficiency before progression.
📚 Supporting research: Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16. [Link]
DictaLearn provides real-time pronunciation scoring within seconds of each exercise. This immediate feedback approach is supported by research showing that prompt corrective feedback is more effective than delayed feedback for motor skill learning (including speech production).
📚 Supporting research: Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189. [Link]
DictaLearn offers three practice modes—Read Aloud (pronunciation), Repeat Audio (fluency and accent), and Type Audio (listening comprehension). While designed intuitively to target different skills, this varied approach aligns with research showing that multimodal learning can improve retention and transfer.
📚 Mayer, R. E. (2009). Cambridge University Press.
DictaLearn uses industry-standard automatic speech recognition (ASR) technology to analyze pronunciation:
📚 Technical reference: Web Speech API Documentation. [MDN Web Docs]
All voice data is processed transiently and not permanently stored on our servers. Free-tier users benefit from client-side processing (data never leaves the browser), while Pro users' audio is processed server-side and immediately deleted after scoring. We prioritize user privacy above all else.
Engineered by an experienced software developer with production-focused practices:
DictaLearn tracks user progress through multiple metrics:
We are conducting small-scale pilot studies with early adopters to validate effectiveness:
Note: As an early-stage platform, we are actively collecting pilot data. Results will be published here when available, with full transparency about sample size and limitations.
Intuitive Design: DictaLearn was built intuitively by a solo developer solving a personal problem, not designed by linguists or learning scientists. The features were created based on practical needs and common sense, then later validated against academic research. The citations above represent post-hoc alignment, not the original design process.
Solo Developer: This platform is independently engineered by a software developer, not a team of phonetics experts. Technical execution is professional, but educational methodology is grounded in established research rather than original academic contributions.
Early Stage: As an MVP-phase platform, we have limited user data and are actively collecting pilot results. Any future claims about user improvement will be backed by verifiable data with transparent sample sizes and methodology.
ASR Accuracy: Automatic speech recognition technology, while improving rapidly, is not perfect. Accuracy varies based on accent, background noise, microphone quality, and other factors.
Individual Variation: Learning outcomes depend on many factors including practice frequency, baseline proficiency, motivation, and individual learning style. Results will vary between users.
Bloom, B. S. (1984). The 2 sigma problem: The search for methods of group instruction as effective as one-to-one tutoring. Educational Researcher, 13(6), 4–16.
https://doi.org/10.3102/0013189X013006004Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132(3), 354–380.
https://doi.org/10.1037/0033-2909.132.3.354Mayer, R. E. (2009). Multimedia Learning (2nd ed.). Cambridge University Press.
https://doi.org/10.1017/CBO9780511811678Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78(1), 153–189.
https://doi.org/10.3102/0034654307313795Web Speech API Documentation. Mozilla Developer Network.
https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_APISee how these research-backed principles work in practice. Try DictaLearn's free tier or join our beta program to help shape the future of pronunciation learning.
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