Speech Recognition Gets an AutoML Training Tool

AutoML, the application of machine learning to create new automation tools, is branching out to new use cases, making itself useful for particularly tedious data science tasks when training speech recognition models. Among the latest attempts at automating the data science workflow is an AutoML tool from Deepgram, offering what the speech recognition vendor claims is a new model training framework for machine transcription. The startup's investors include Nvidia GPU Ventures and In-Q-Tel, the venture arm of the U.S. intelligence community. Deepgram's flagship platform scans audio data to train a speech recognition tool. Its deep learning tool uses a hybrid convolutional/recurrent neural network approach, training models via GPU accelerators.