At Nuance, we empower people with the ability to seamlessly interact with their connected devices and the digital world around them. We are creating a world where technology thinks and acts the way people do by designing the most human, natural, and intuitive ways of interacting with technology.
Our nimble technology uses analytics and advanced algorithms to transform the inanimate into animate and reduce complicated processes into simple ones.
Join our Corporate Research team to advance the cutting edge technology and make future intelligent interfaces even smarter.
Summary: Evaluate the usage patterns of Nuance customers via big data analysis; build models to improve core ASR accuracy of individual products; contribute to the model building codebase, including our deep learning toolkit; and stay current on state-of-the-art algorithms in related fields. Work on challenging research problems that have a concrete impact on real-world applications, such as in-car assistants and home entertainment systems.
• Conducting experiments to assess the quality of language models and study the effect of language modeling variants and ancillary natural language processing technology (such as auto-punctuation) on speech recognition accuracy.
• Identifying, optimizing, and clustering training data.
• Analyzing product usage data to identify areas of possible improvement or enhancement of language modeling process, method, and NLP techniques.
• Implementation of improved training recipes and NLP prototypes utilizing C/C++, Perl, and Python.
• Discussing and presenting ideas, progress, and results within the research team
• Improving language modeling performance in multiple languages, especially Chinese
• MS or PhD, with 2+ years of professional development experience preferred
• Background in speech technology, statistical machine translation, or natural language processing
• Excellent programming skills (C/C++, Python) with knowledge of standard data structures and algorithms
• Experience using Unix/Linux and shell scripting
• Solid written and oral communication skills (English)
• Explicit (industry or academic) experience with large vocabulary speech recognition
• Expertise in one or more of the following areas: machine learning, statistical modeling, deep learning, numerical optimization, data mining, algorithm design, software engineering, computational linguistics
Education: Advanced degree (Masters or PhD) in computer science, computational linguistics, applied mathematics, or a related field