Publication

Robust Multi-Channel Speech Recognition using Frequency Aligned Network

By Taejin Park, Kenichi Kumatani, Minhua Wu, Shiva Sundaram
2020
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Abstract
Conventional speech enhancement techniques such as beamforming have known benefits for far-field speech recognition. Our own work in frequency-domain multi-channel acoustic modeling has shown additional improvements by training a spatial filtering layer jointly within an acoustic model. In this paper, we further develop this idea and use a frequency-aligned network for robust multi-channel automatic speech recognition (ASR). Unlike an affine layer in the frequency domain, the proposed frequency-aligned component prevents one frequency bin influencing other frequency bins. We show that this modification not only reduces the number of parameters in the model but also significantly improves the ASR performance. We investigate effects of frequency-aligned networks through ASR experiments on the real-world far-field data where users are interacting with an ASR system in uncontrolled acoustic environments. We show that our multi-channel acoustic model with a frequency-aligned network shows up to 18% relative reduction in word error rate.
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Sr. Applied Scientist
US, WA, Seattle
We are constantly making Alexa the best voice assistant in the world. Amazon’s Alexa cloud service and Echo devices are used every day, by people you know, in and about their homes. The Alexa Monetization team is hiring talented and experienced Sr. Applied Scientists to help building the next generation products for Alexa across multiple channels and domains. We are seeking an experienced, entrepreneurial, big thinker for a confidential new initiative within Alexa. You will be joining a team doing innovative work, making a direct impact to customers, showing measurable success, and building with the latest natural language processing systems. If you are holding out for an opportunity to:Make a huge impact as an individual· Be part of a team of smart and passionate professionals who will challenge you to grow every day· Solve difficult challenges using your expertise in coding elegant and practical solutions· Create applications at a massive scale used by millions of people· Work with machine learning systems to deliver real experiences, not just researchAnd you are experienced with…· Drive applied science (machine learning) projects end-to-end ~ from ideation, analysis, prototyping, development, metrics, and monitoring· Conduct deep analyses on massive user and contextual data sets· Propose viable modeling ideas to advance optimization or efficiency, with supporting argument, data, or, preferably, preliminary results· Design, develop, and maintain scalable, Machine Learning models with automated training, validation, monitoring and reporting· Stay familiar with the field and apply state-of-the-art Machine Learning techniques to NLP and related optimization problems· Produce peer-reviewed scientific paper in top journals and conferencesAnd you constantly look for opportunities to…· Innovate, simplify, reduce waste, and increase efficiencies· Use data to make decisions and validate assumptions· Automate processes otherwise performed by humans· Learn from others and help grow those around you...then we would love to chat!In 2021, we have the opportunity to build new products and features from the ground up and we are looking for strong, bias for action engineering leaders who are not afraid of taking bold bets and trying new things to improve customer experience for Alexa.As part of a new and growing team, you will be iterating on new features and products to help drive innovation and expansion. You will work on cross-functional and cross-domain opportunities; tackle challenging projects aim to accelerate experimentations in Alexa; and build out operating mechanisms and technology to enable novel customer experiences. You will be instrumental in setting the team culture, quality bar, engineering best practices, and norms. Mentoring and growing the team around you will be one of the primary ways you measure your own success. You will have the opportunity to contribute and develop deep expertise in the areas of distributed systems, machine learning, conversational technologies, user interfaces (including voice and natural user interfaces), data storage and data pipelines.This role is exciting for scientists who love to apply startup mindset to their day-to-day, enjoy working cross-functionally to master both business and technology knowledge, and are passionate about building engineering best practices. If you are looking for opportunity to learn, grow and lead, this is the position for you.
View from space of a connected network around planet Earth representing the Internet of Things.
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