Publications

A Framework for Speech Recognition Benchmarking

Proc. of Interspeech 2018

Publication date: September 2, 2018

Franck Dernoncourt, Trung Bui, Walter Chang

Over the past few years, the number of APIs for automated speech recognition (ASR) has significantly increased. It is often time-consuming to evaluate how the performance of these ASR systems compare with each other, and against newly proposed algorithms. In this paper, we present a lightweight, open source framework that allows users to easily benchmark ASR APIs on the corpora of their choice. The framework currently supports 7 ASR APIs and is easily extendable to more APIs.

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Research Areas:  Adobe Research iconAI & Machine Learning Adobe Research iconAudio