Intern – Speech Processing / ASR for Low-Resource Languages

Summary

Leidos is an industry and technology leader serving government and commercial customers with smarter, more efficient digital and mission innovations. This internship will support research and development efforts focused on audio enhancement, speech activity detection, and automatic speech recognition (ASR) for low-resource languages.

Responsibilities

• Support Leidos engineers and researchers in defining tasks, workflows, and integration requirements
• Assist with designing and implementing a prototype pipeline to transform noisy audio into data usable by downstream speech models
• Help preprocess, enhance, segment, and analyze noisy audio for low-resource language applications
• Run experiments, evaluate results, and document findings
• Prepare technical content and communicate progress, challenges, and next steps in team meetings, design reviews, and technical exchanges
• Contribute to testing, prototyping, and iterative improvement of speech and audio processing workflows

Skills

• Current advanced undergraduate (rising junior or rising senior) or graduate student studying Computational Linguistics, Speech and Hearing Sciences, Acoustics, Electrical Engineering, Computer Science, Data Science, or a related technical field
• Coursework, academic project experience, lab experience, or other hands-on experience in one or more of the following: speech processing, audio signal processing, machine learning, natural language processing, acoustic phonetics or a related area
• Experience programming in Python through coursework, research, projects, or internships
• Strong problem-solving skills and the ability to communicate technical results clearly
• U.S. Citizenship required
• Coursework, project work, or research experience in one or more of the following: audio enhancement, speech activity detection, speaker diarization, speaker identification, ASR, or low-resource language technologies
• Familiarity with speech, audio, or machine learning tools and frameworks such as PyTorch, TensorFlow, torchaudio, Kaldi, ESPnet, SpeechBrain, Hugging Face, or similar
• Experience working with noisy, conversational, far-field, or otherwise real-world audio data
• Familiarity with data preparation, annotation workflows, corpus curation, or model bootstrapping approaches
• Familiarity with AWS or other cloud-based development environments
• Publications, class projects, research posters, GitHub projects, or other demonstrable technical work in a relevant area

Qualifications

Must Haves

• Current advanced undergraduate (rising junior or rising senior) or graduate student studying Computational Linguistics, Speech and Hearing Sciences, Acoustics, Electrical Engineering, Computer Science, Data Science, or a related technical field
• Coursework, academic project experience, lab experience, or other hands-on experience in one or more of the following: speech processing, audio signal processing, machine learning, natural language processing, acoustic phonetics or a related area
• Experience programming in Python through coursework, research, projects, or internships
• Strong problem-solving skills and the ability to communicate technical results clearly
• U.S. Citizenship required

Nice to Haves

• Coursework, project work, or research experience in one or more of the following: audio enhancement, speech activity detection, speaker diarization, speaker identification, ASR, or low-resource language technologies
• Familiarity with speech, audio, or machine learning tools and frameworks such as PyTorch, TensorFlow, torchaudio, Kaldi, ESPnet, SpeechBrain, Hugging Face, or similar
• Experience working with noisy, conversational, far-field, or otherwise real-world audio data
• Familiarity with data preparation, annotation workflows, corpus curation, or model bootstrapping approaches
• Familiarity with AWS or other cloud-based development environments
• Publications, class projects, research posters, GitHub projects, or other demonstrable technical work in a relevant area

Benefits

• Health and Wellness programs
• Income Protection
• Paid Leave
• Retirement