Pith. sign in

REVIEW

What shall we do with an hour of data? Speech recognition for the un- and under-served languages of Common Voice

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2105.04674 v1 pith:M3TF6CYI submitted 2021-05-10 cs.CL cs.LGcs.SDeess.AS

Francis M. Tyers , Josh Meyer This is my paper · ORCID
classification cs.CLcs.LGcs.SDeess.AS
keywords modelsrecognitionspeechcommonlanguagesunder-servedvoiceaccuracy
verification ladder T0 review T1 audit T2 compute T3 formal

Signed reviews

No signed human review yet.

0 comments
read the original abstract

This technical report describes the methods and results of a three-week sprint to produce deployable speech recognition models for 31 under-served languages of the Common Voice project. We outline the preprocessing steps, hyperparameter selection, and resulting accuracy on official testing sets. In addition to this we evaluate the models on multiple tasks: closed-vocabulary speech recognition, pre-transcription, forced alignment, and key-word spotting. The following experiments use Coqui STT, a toolkit for training and deployment of neural Speech-to-Text models.

Discussion (0). Continue with ORCID to comment.

Pith tools