Senior Research Scientist-Language Modeling
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.
Responsibilities:
• 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
Qualifications
Required Skills:
• 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)
Preferred Skills:
• 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
简历投递： [email protected]
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.
Responsibilities:
• 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
Qualifications
Required Skills:
• 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)
Preferred Skills:
• 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
简历投递： [email protected]
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