Data entry ops · Production

super.AI accelerates audio data annotation to scale Lalilo's speech recognition dataset

The problem

Lalilo needed to build and annotate a large corpus of children's speech recordings from scratch to train a mispronunciation-detection model, but almost no annotated corpora of children's recordings existed and their internal annotation process could not keep up with the volume required.

Workflow diagram · grounded in source
1
Lalilo seeks annotation partner
trigger
“their turnaround time for the large volumes of data they needed to annotate was not sustainable so they started looking for a partner to help them with this”
2
Humans & AI annotation at scale
ai_action
“our Humans & AI solution, were were able to handle a much larger volume of data and annotate it at a significantly faster turnaround time. Thanks to our large crowd, we were able to provide Lalilo with a higher number of annotators than …”
3
Custom format delivery
output
“customised solution to them, adjusted to their data inputs and providing the data output in their desired format”
4
Speech recognition model training
integration
“improving the required accuracy needed to train their speech recognition system”
Reported outcome

Lalilo significantly scaled their dataset of children's speech recordings and improved the accuracy needed to train their speech recognition system, with super.AI delivering annotated data at a significantly faster turnaround time.

Reported metrics
Dataset scalesignificantly scale their internal dataset
Annotation turnaround timesignificantly faster turnaround time
Annotation accuracyhigher quality of accuracy
Reported stack
Humans & AI solution
Source
https://super.ai/case-studies/lalilo
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Lalilo significantly scaled their dataset of children's speech recordings and improved the accuracy needed to train their speech recognition system, with super.AI delivering annotated data at a significantly faster tu…

What tools did this team use?

Humans & AI solution.

What results were reported?

Dataset scale: significantly scale their internal dataset; Annotation turnaround time: significantly faster turnaround time; Annotation accuracy: higher quality of accuracy (source-reported, not independently verified).

How is this data entry ops AI workflow structured?

Lalilo seeks annotation partner → Humans & AI annotation at scale → Custom format delivery → Speech recognition model training.

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