Self-service Platform for building Speech Recognition Models
Our tech leadership contributed to an open source ASR toolkit which can be used to build state of the art ASR models from scratch using lesser resources and faster roll outs resulting in AI innovation in spoken languages
Built an end to end MLOps pipeline for building datasets and deep learning models for Speech recognition.
Provided thought leadership on data strategy and created strategies for data acquisition, data
analysis, data filtering, data identification of audio datasets.
The platform was built on GCP and airflow for building the orchestration pipeline.
All the required infrastructure could be built just by running few commands using Terraform
Tech: MLFlow, Kubernetes, Airflow, Python, MongoDB, Postgres, GCP, Terraform