Speech Recognition

As a scientist on the Machine Learning and Speech Processing team at CaptionCall, I developed algorithms and implemented machine learning and natural language processing techniques to improve automatic speech recognition for telephone captioning, resulting in deployment and three patents. My contributions included:

• Successfully developed novel techniques for training n-gram language models on the fly without saving transcriptions, including techniques that make use of interpolation and neural net text sampling.                                                                                                             

• Implemented natural language processing and deep learning methods to estimate transcription quality with an average mean absolute error of 1.6% (more than ten times smaller than state-of-the-art estimators at the time). 

• Collaborated in implementing real-time fusion of multiple transcripts for improved accuracy. Contributed quality estimation of transcripts using support vector machines for enhanced voting and tie-breaking decisions, improving accuracy by 5% on average.