# My Science Tutor (MyST) -- A Large Corpus of Children's Conversational Speech

arXiv: https://arxiv.org/abs/2309.13347 · HTML: https://mlsanity.com/paper/2309.13347/

## Key facts

- Cited by 28 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 17 references that are in the map.
- First posted on arXiv 23 Sep 2023.

## Builds on (most cited first, 2 of 2)

- [SpeechBrain: A General-Purpose Speech Toolkit](https://mlsanity.com/paper/2106.04624/) (2021)
- [End-to-End Neural Systems for Automatic Children Speech Recognition: An Empirical Study](https://mlsanity.com/paper/2102.09918/) (2021)

## Built on by (most cited first, 28 of 28)

- [SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Words](https://mlsanity.com/paper/2406.13340/) (2024)
- [TTSDS2: Resources and Benchmark for Evaluating Human-Quality Text to Speech Systems](https://mlsanity.com/paper/2506.19441/) (2025)
- [Hallucination Benchmark for Speech Foundation Models](https://mlsanity.com/paper/2510.16567/) (2025)
- [Self-Supervised Models for Phoneme Recognition: Applications in Children's Speech for Reading Learning](https://mlsanity.com/paper/2503.04710/) (2025)
- [Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet](https://mlsanity.com/paper/2508.16576/) (2025)
- [Children's Speech Recognition through Discrete Token Enhancement](https://mlsanity.com/paper/2406.13431/) (2024)
- [SSVD: Structured SVD for Parameter-Efficient Fine-Tuning and Benchmarking under Domain Shift in ASR](https://mlsanity.com/paper/2509.02830/) (2025)
- [TICL+: A Case Study On Speech In-Context Learning for Children's Speech Recognition](https://mlsanity.com/paper/2512.18263/) (2025)
- [SALSA: Speech Aware LLM Adaptation via Learned Steering Activation Vectors](https://mlsanity.com/paper/2606.00460/) (2026)
- [FASA: a Flexible and Automatic Speech Aligner for Extracting High-quality Aligned Children Speech Data](https://mlsanity.com/paper/2406.17926/) (2024)
- [Automatic Screening for Children with Speech Disorder using Automatic Speech Recognition: Opportunities and Challenges](https://mlsanity.com/paper/2410.11865/) (2024)
- [TICL: Text-Embedding KNN For Speech In-Context Learning Unlocks Speech Recognition Abilities of Large Multimodal Models](https://mlsanity.com/paper/2509.13395/) (2025)
- [Large Language Models based ASR Error Correction for Child Conversations](https://mlsanity.com/paper/2505.16212/) (2025)
- [Towards Pretraining Robust ASR Foundation Model with Acoustic-Aware Data Augmentation](https://mlsanity.com/paper/2505.20606/) (2025)
- [SimClass: A Classroom Speech Dataset Generated via Game Engine Simulation For Automatic Speech Recognition Research](https://mlsanity.com/paper/2506.09206/) (2025)
- [SSVD-O: Parameter-Efficient Fine-Tuning with Structured SVD for Speech Recognition](https://mlsanity.com/paper/2601.12600/) (2026)
- [MetaSICL: Globalizing Auditory LLMs for Underserved Speakers and Languages via Meta Speech In-Context Learning](https://mlsanity.com/paper/2601.18904/) (2026)
- [Entropy-Aware Domain-Routed Mixture-of-Experts Speech-LLM Framework: A Case Study of Multi-Domain Child-Adult ASR](https://mlsanity.com/paper/2606.10454/) (2026)
- [Causal Structure Discovery for Error Diagnostics of Children's ASR](https://mlsanity.com/paper/2506.00402/) (2025)
- [RealClass: A Framework for Classroom Speech Simulation with Public Datasets and Game Engines](https://mlsanity.com/paper/2510.01462/) (2025)
- [KidSpeak: A General Multi-purpose LLM for Kids' Speech Recognition and Screening](https://mlsanity.com/paper/2512.05994/) (2025)
- [Abjad-Kids: An Arabic Speech Classification Dataset for Primary Education](https://mlsanity.com/paper/2603.20255/) (2026)
- [When AI Meets Early Childhood Education: Large Language Models as Assessment Teammates in Chinese Preschools](https://mlsanity.com/paper/2603.24389/) (2026)
- [Child-Centric Voice Anonymization in Single and Multi-Speaker Speech via Domain-Adapted SSL Models](https://mlsanity.com/paper/2606.29897/) (2026)
- [Encoder Awakening via Adapters: Effective Domain-Adaptive Fine-tuning of Speech-LLMs](https://mlsanity.com/paper/2609.17981/) (2026)
- [Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speech](https://mlsanity.com/paper/2609.33060/) (2026)
- [AraYoungVoices: A Diverse L1/L2 Corpus of Arabic Child and Adolescent Speech](https://mlsanity.com/paper/2610.05044/) (2026)
- [Child ASR Adaptation with Adult Retention: An Empirical Study](https://mlsanity.com/paper/2610.08827/) (2026)

## Abstract (arXiv)

This article describes the MyST corpus developed as part of the My Science Tutor project -- one of the largest collections of children's conversational speech comprising approximately 400 hours, spanning some 230K utterances across about 10.5K virtual tutor sessions by around 1.3K third, fourth and fifth grade students. 100K of all utterances have been transcribed thus far. The corpus is freely available (https://myst.cemantix.org) for non-commercial use using a creative commons license. It is also available for commercial use (https://boulderlearning.com/resources/myst-corpus/). To date, ten organizations have licensed the corpus for commercial use, and approximately 40 university and other not-for-profit research groups have downloaded the corpus. It is our hope that the corpus can be used to improve automatic speech recognition algorithms, build and evaluate conversational AI agents for education, and together help accelerate development of multimodal applications to improve children's excitement and learning about science, and help them learn remotely.