Speech-recognition and pronunciation apps let learners read at any time and receive an immediate result. If AI can listen, does a learner still need another person to hear them?

We do not have to choose so quickly. AI and people are not competing for exactly the same role. AI can become a tireless practice partner. A person can notice what the learner was trying to communicate and how today’s reading differs from yesterday’s. The useful question is not which is better, but which kind of support this learner needs now.

AI Makes Another Attempt Easy

Automatic speech recognition (ASR) converts speech into text and, in some systems, analyses features of pronunciation. Learners can record themselves repeatedly in private and receive a response without waiting for a teacher.

A meta-analysis of 15 studies found a moderate overall benefit of ASR-based practice for ESL/EFL pronunciation. The results were not uniform. Effects were larger when systems provided explicit corrective feedback, larger for individual sounds than for stress, rhythm, and intonation, and larger in peer-supported conditions than in individual practice (Ngo, Chen, & Lai, 2024).

AI can increase practice and noticing.
But a recognition result does not measure everything that makes speech understandable.

A Correct Transcript Is Not a Perfect Pronunciation Score

When a system transcribes a learner’s words correctly, it can provide encouraging evidence that the message was recognised. Yet an ASR system is not the same as a human conversation partner. It may infer a word from context, reject speech that people understand, or successfully transcribe speech whose phrasing still feels difficult to follow.

Modern systems have improved greatly. A 2025 study tested several current systems on read and spontaneous English produced by speakers from six first-language backgrounds. Some systems approached human-level accuracy for the read sentences, but performance still differed by system, first-language background, and speech task (McGuire, 2025). Even as technology improves, one score or transcript should remain evidence to investigate, not a final verdict.

A Human Coach Hears More Than Sounds

A person hears not only whether each word is accurate, but also the meaning groups, ease of listening, hesitation, effort, and change over time. A Coach can decide not to correct everything and select one point that is useful now.

In a study of 61 Chinese learners of English, a group using ASR with peer correction improved more than a group receiving conventional teacher-led instruction on several pronunciation and speaking measures. This does not prove that AI is better than people. It suggests that a combination of technology and human interaction can be productive (Sun, 2023).

ONDEN’s eight minutes of being heard therefore offer something different from a score. Someone receives the learner’s effort and helps close the session with “I did it today.” The Coach does not have to become a perfect pronunciation teacher; the Coach can be the listener who helps practice continue.

Give AI and the Coach Different Jobs

When both are available, their roles can be separated:

If AI and the Coach respond differently, one does not automatically have to be wrong. Asking why they differed can deepen attention to sounds, prominence, phrasing, and the listener.

An Eight-Minute AI–Human Routine

No AI is required for this principle to work. A learner can mark a doubtful pronunciation, finish the passage, and investigate it afterwards. Choosing not to stop for every uncertainty protects both the flow of reading and the learner’s agency.

Questions ONDEN Wants to Test

The studies above do not directly test ONDEN’s eight-minute model. Future practice and data can examine:

Summary

AI and human Coaches do not have to replace one another.

  • AI can support repeated practice and immediate noticing
  • recognition results are useful evidence, not absolute pronunciation judgements
  • people can hear meaning, ease, effort, and change together
  • separate roles can combine the speed of AI with human connection

AI can analyse a voice.
A person can receive it.

References

  • McGuire, M. (2025). Automatic speech recognition for non-native English: Accuracy and disfluency handling. arXiv. https://doi.org/10.48550/arXiv.2503.06924
  • Ngo, T. T.-N., Chen, H. H.-J., & Lai, K. K.-W. (2024). The effectiveness of automatic speech recognition in ESL/EFL pronunciation: A meta-analysis. ReCALL, 36(1), 4–21.
  • Sun, W. (2023). The impact of automatic speech recognition technology on second language pronunciation and speaking skills of EFL learners: A mixed methods investigation. Frontiers in Psychology, 14, 1210187.