https://www.amazon.science/blog/why-alexa-wont-wake-up-when-she-hears-her-name-in-amazons-super-bowl-ad * Research areas + Automated reasoning + Cloud and systems + Computer vision + Conversational AI / Natural-language processing + Economics + Information and knowledge management + Machine learning + Operations research and optimization + Quantum technologies + Robotics + Search and information retrieval + Security, privacy, and abuse prevention + Sustainability + Automated reasoning + Cloud and systems + Computer vision + Conversational AI / Natural-language processing + Economics + Information and knowledge management + Machine learning + Operations research and optimization + Quantum technologies + Robotics + Search and information retrieval + Security, privacy, and abuse prevention + Sustainability * Blog * News and features + Awards and recognitions + Awards and recognitions * Publications * Conferences * Collaborations + Alexa Prize + Amazon Research Awards + Amazon SURE + Alexa Prize + Amazon Research Awards + Amazon SURE * Careers + Academics at Amazon + Internships + Working at Amazon + Academics at Amazon + Internships + Working at Amazon [] Subscribe Follow Us * twitter * instagram * youtube * facebook * linkedin Menu amazon-science-logo.svg * Research areas + Automated reasoning + Cloud and systems + Computer vision + Conversational AI / Natural-language processing + Economics + Information and knowledge management + Machine learning + Operations research and optimization + Quantum technologies + Robotics + Search and information retrieval + Security, privacy, and abuse prevention + Sustainability + Automated reasoning + Cloud and systems + Computer vision + Conversational AI / Natural-language processing + Economics + Information and knowledge management + Machine learning + Operations research and optimization + Quantum technologies + Robotics + Search and information retrieval + Security, privacy, and abuse prevention + Sustainability * Blog * News and features + Awards and recognitions + Awards and recognitions * Publications * Conferences * Collaborations + Alexa Prize + Amazon Research Awards + Amazon SURE + Alexa Prize + Amazon Research Awards + Amazon SURE * Careers + Academics at Amazon + Internships + Working at Amazon + Academics at Amazon + Internships + Working at Amazon [] Subscribe Search [ ] Submit Search Conversational AI / Natural-language processing Why Alexa won't wake up when she hears her name in Amazon's Super Bowl ad By Mike Rodehorst January 31, 2019 Share Share * Copy link * Email * Twitter * LinkedIn * Facebook * Line * Reddit * QZone * Sina Weibo * WeChat * WhatsApp Fen Xiang Dao Wei Xin x https://www.amazon.science/blog/ why-alexa-wont-wake-up-when-she-hears-her-name-in-amazons-super-bowl-ad This Sunday's Super Bowl between the New England Patriots and the Los Angeles Rams is expected to draw more than 100 million viewers, some of whom will have Alexa-enabled devices within range of their TV speakers. When Amazon's new Alexa ad airs, and Forest Whitaker asks his Alexa-enabled electric toothbrush to play his podcast, how will we prevent viewers' devices from mistakenly waking up? QB decision making.png Related content How AWS scientists help create the NFL's Next Gen Stats In its collaboration with the NFL, AWS contributes cloud computing technology, machine learning services, business intelligence services -- and, sometimes, the expertise of its scientists. With the Super Bowl ad -- as with thousands of other media mentions of Alexa tracked by our team -- we teach Alexa what individual recorded instances of her name sound like, so she will know to ignore them. We can also apply this technique, known as acoustic fingerprinting, on the fly to recognize when multiple devices from different households are hearing the same command at around the same time. This is crucial to preventing Alexa from responding to pranks on TV, references to people named Alexa, or other instances of her name in broadcast media that we don't know about in advance. Audio_watermark.gif._CB468320145_.gif Related content Audio watermarking algorithm is first to solve "second-screen problem" in real time Audio watermarking is the process of adding a distinctive sound pattern -- undetectable to the human ear -- to an audio signal to make it identifiable to a computer. It's one of the ways that video sites recognize copyrighted recordings that have been posted illegally. To identify a watermark, a computer usually converts a digital file into an audio signal, which it processes internally. Our approach to matching audio recordings is based on classic acoustic-fingerprinting algorithms like that of Haitsma and Kalker in their 2002 paper "A Highly Robust Audio Fingerprinting System". Such algorithms are designed to be robust to audio distortion and interference, such as those introduced by TV speakers, the home environment, and our microphones. To produce an acoustic fingerprint, we first derive a grid of log filter-bank energies (LFBEs) for the acoustic signal, which represent the amounts of energy in multiple overlapping frequency bands in a series of overlapping time windows. The algorithm steps through the grid in two-by-two blocks and adds and subtracts the measurements in the grid cells in a standardized way. (Technically, it computes the 2-D gradient of each block.) The sign of the result -- positive or negative -- provides a one-bit summary of the values in the block. The summaries of all the blocks in the grid constitute the acoustic fingerprint, and two fingerprints are deemed to match if the fraction of bits that are different (the "bit error rate") is small enough. Acoustic-fingerprinting_figure.jpg._CB455311870_.jpg An illustration of how fingerprints are used to match audio. Different instances of Alexa's name result in a bit error rate of about 50% (random bit differences). A bit error rate significantly lower than 50% indicates two recordings of the same instance of Alexa's name. When we have audio samples in advance -- as we do with the Super Bowl ad -- we fingerprint the entire sample and store the result. With audio that's streaming to the cloud from Alexa-enabled devices, we build up fingerprints piecemeal, repeatedly comparing them to other fingerprints as they grow. If a match is found, the incoming request is ignored. Noisy audio may yield a match, but it requires the accumulation of more data (a larger fingerprint) than clean audio does. Using this matching algorithm, we have built a system with multiple layers to protect customers at multiple stages: * On-device: On most Echo devices, every time the wake word "Alexa" is detected, the audio is checked against a small set of known instances where Alexa is mentioned in commercials. Due to the limits of device CPU, this set is generally restricted to commercials we expect to be currently airing on TV. * In the cloud: Every audio request to Alexa that starts with a wake word is checked in two ways: + Known media: the audio is checked against a large set of fingerprints for known instances of "Alexa" and other wake words in commercials and other media. These fingerprints can also make use of the audio that follows the wake word. + Unknown media: the audio is checked against a fraction of other Alexa requests arriving at around the same time. If the audio of a request matches that of requests from at least two other customers, we identify it as a media event. We also check incoming audio against a small cache of fingerprints discovered on the fly (the cached fingerprints are averages of the fingerprints that were declared matches). The cache allows Alexa to continue to ignore spurious wake words even when they no longer occur simultaneously. Ideally, a device will identify media audio using locally stored fingerprints, so it does not wake up at all. If it does wake up, and we match the media event in the cloud, the device will quickly and quietly turn back off. In addition to tracking new media mentions of Alexa's name and updating our library of fingerprints accordingly, our team works continuously to improve the accuracy and efficiency of the fingerprinting system. We're also exploring complementary technologies, such as machine learning systems that can distinguish media audio more generally from live human speech. Acknowledgments: Joe Wang, Aaron Challenner, Mike Peterson, Michael Rudeen, Naresh Narayanan, Liangwei Guo, and the rest of the team Research areas * Conversational AI / Natural-language processing Tags * Alexa * Keyword spotting * Signal processing About the Author Mike Rodehorst Mike Rodehorst is a machine learning scientist in the Alexa Speech group. Related content * CTC architecture-high-res.16x9.png Teaching speech recognizers new words -- without retraining Sravan Bodapati January 13, 2023 Using lists of rare or out-of-vocabulary words to bias connectionist temporal classification models enables personalization. Conversational AI / Natural-language processing * An aerial shot of the Tennessee State University on a sunny day Tennessee State University Amazon and Tennessee State University announce collaboration Staff writer January 12, 2023 The collaboration, housed in the College of Engineering, includes funds for faculty research projects, with an initial focus on AI, robotics, and operations research. Robotics * PATE for ASR framework.png Better differential privacy for end-to-end speech recognition Huck Yang, Andreas Stolcke January 11, 2023 Private aggregation of teacher ensembles (PATE) leads to word error rate reductions of more than 26% relative to standard differential-privacy techniques. Conversational AI / Natural-language processing Work with us See more jobs See more jobs Economist - II, PXT Central Science US, VA, Arlington The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to work with business partners to hone complex problems into specific, scientific questions, and test those questions to generate insights. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work closely with business partners to develop science that solves the most important business challenges. They will work in a team setting with individuals from diverse disciplines and backgrounds. They will serve as an ambassador for science and a scientific resource for business teams, so that scientific processes permeate throughout the HR organization to the benefit of Amazonians and Amazon. Ideal candidates will own the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. Economist, PXT Central Science US, WA, Seattle The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal. We are looking for economists who are able to apply economic methods to address business problems. The ideal candidate will work with engineers and computer scientists to estimate models and algorithms on large scale data, design pilots and measure their impact, and transform successful prototypes into improved policies and programs at scale. We are looking for creative thinkers who can combine a strong technical economic toolbox with a desire to learn from other disciplines, and who know how to execute and deliver on big ideas as part of an interdisciplinary technical team. Ideal candidates will work in a team setting with individuals from diverse disciplines and backgrounds. They will work with teammates to develop scientific models and conduct the data analysis, modeling, and experimentation that is necessary for estimating and validating models. They will work closely with engineering teams to develop scalable data resources to support rapid insights, and take successful models and findings into production as new products and services. They will be customer-centric and will communicate scientific approaches and findings to business leaders, listening to and incorporate their feedback, and delivering successful scientific solutions. Key job responsibilities Use causal inference methods to evaluate the impact of policies on employee outcomes. Examine how external labor market and economic conditions impact Amazon's ability to hire and retain talent. Use scientifically rigorous methods to develop and recommend career paths for employees. A day in the life Work with teammates to apply economic methods to business problems. This might include identifying the appropriate research questions, writing code to implement a DID analysis or estimate a structural model, or writing and presenting a document with findings to business leaders. Our economists also collaborate with partner teams throughout the process, from understanding their challenges, to developing a research agenda that will address those challenges, to help them implement solutions. About the team We are a multidisciplinary team that combines the talents of science and engineering to develop innovative solutions to make Amazon Earth's Best Employer. Postdoctoral Scientist - Machine Learning US, WA, Seattle Amazon is looking for talented Postdoctoral Scientists to join our global Science teams for a one-year, full-time research position. Postdoctoral Scientists will innovate as members of Amazon's key global Science teams, including: AWS, Alexa AI, Alexa Shopping, Amazon Style, CoreAI, Last Mile, and Supply Chain Optimization Technologies. Postdoctoral Scientists will join one of may central, global science teams focused on solving research-intense business problems by leveraging Machine Learning, Econometrics, Statistics, and Data Science. Postdoctoral Scientists will work at the intersection of ML and systems to solve practical data driven optimization problems at Amazon scale. Postdocs will raise the scientific bar across Amazon by diving deep into exploratory areas of research to enhance the customer experience and improve efficiencies. Please note: This posting is one of several Amazon Postdoctoral Scientist postings. Please only apply to a maximum of 2 Amazon Postdoctoral Scientist postings that are relevant to your technical field and subject matter expertise. Key job responsibilities * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon's vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. 2023 Applied Scientist - Intern AU Are you excited about understanding the state-of-the-art Machine Learning, Natural Language Processing, Deep Learning and Computer Vision algorithms and designs using large data sets to solve real world problems? A research internship at Amazon is an opportunity to work with leading machine learning researchers on incomparable datasets using the best tools and hardware in the world. It is an opportunity for PhD students and recent PhD graduates in Computer Vision, Deep Learning, Natural Language Processing, and broader Machine Learning to address challenges at a scale that is impossible elsewhere. Along the way, you'll get opportunities to be a disruptor, prolific innovator, and a reputed problem solver--someone who truly enables machine learning to create significant impact. As an Applied Scientist Intern, you will be working in a fast-paced, cross-disciplinary team of researchers who are pioneers in the field. You will take on complex problems, and work on solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products. Amazon Robotics - Applied Scientist Intern/Co-op - 2023 US, MA, Westborough Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you'll fit right in here at Amazon Robotics. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers' experiences in ways we can't even imagine yet. We invent new improvements every day. We are Amazon Robotics and we will give you the tools and support you need to invent with us in ways that are rewarding, fulfilling and fun. Amazon Robotics is seeking interns and co-ops with a passion for robotic research to work on cutting edge algorithms for robotics. Our team works on challenging and high-impact projects, including allocating resources to complete a million orders a day, coordinating the motion of thousands of robots, autonomous navigation in warehouses, identifying objects and damage, and learning how to grasp all the products Amazon sells. We are seeking internship candidates with backgrounds in computer vision, machine learning, resource allocation, discrete optimization, search, and planning/scheduling. You will be challenged intellectually and have a good time while you are at it! Please note that by applying to this role you would be considered for Applied Scientist summer intern, spring co-op, and fall co-op roles on various Amazon Robotics teams. These teams work on robotics research within areas such as computer vision, machine learning, robotic manipulation, navigation, path planning, perception, artificial intelligence, human-robot interaction, optimization and more. 2023 Research Science Internship - Quantum Computing IL, Tel Aviv Are you a MS or PhD student interested in a 2023 Research Science Internship, where you would be using your experience to initiate the design, development, execution and implementation of scientific research projects? If you're insatiably curious and always want to learn more, then you've come to the right place. Depending on your location, country, job status and other requirements, some or all of the following benefits may be available to you as an intern. * Competitive pay * Impactful project and internship/role deliverables * Hybrid working (team dependent) * Networking opportunities with fellow interns * Internships events such as speaker series, intern panels, Leadership Principles sessions, Amazon writing skills sessions. * Mentorship and career development If this describes you, come join our research teams at Amazon. We are looking for motivated students with research interests in a variety of science domains to build state-of-the-art solutions for never before solved problems. If you're successful during your internship, you could be considered for a graduate role after finishing your university studies Internship start dates vary throughout the year. Internship length can vary between 3 - 6 months for Full Time and 6 - 12 months for Part Time. Key job responsibilities * Work closely with scientists and engineering teams (position-dependent) * Work on an interdisciplinary team on customer-obsessed research * Design new algorithms, models, or other technical solutions * Experience Amazon's customer-focused culture Amazon Postdoctoral Scientist , EU ATS Research Science LU, Luxembourg Have you ever wondered how Amazon delivers timely and reliably hundreds of millions of packages to customer's doorsteps? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! Amazon Transportation Services is seeking a Postdoctoral Scientist with Operations Research or Applied Mathematics background, to join our team in the EU Headquarters in Luxembourg, for a one-plus-one year full-time research position. As a key member of the EU Research Science Team, this person will be responsible for designing and implementing beyond state of the art algorithmic frameworks that optimize the middle-mile Amazon Transportation Network. The successful applicant will ensure that our end-to-end strategies in terms of customer demand fulfillment, routing, consolidation locations, linehaul/airhaul/sea options and last-mile transportation are streamlined and optimized Key job responsibilities In this role you will: * Work closely with a senior science advisor, collaborate with other scientists and engineers, and be part of Amazon's vibrant and diverse global science community. * Publish your innovation in top-tier academic venues and hone your presentation skills. * Be inspired by challenges and opportunities to invent cutting-edge techniques in your area(s) of expertise. Applied Scientist, Ring NL, Amsterdam Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique possibility to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer. You will be part of a team committed to pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors. This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work on scale. This position requires experience with developing efficient computer vision algorithms on resource-constrained computing platforms on edge. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms. Key job responsibilities * Research and implement the state-of-the-art computer vision and sensor fusion algorithms for resource-constrained computing platforms on a large scale. * Collaborate with product managers and engineering teams to design and implement computer vision and machine learning based features for Ring devices * Influence system design and product vision by making informed decisions on the selection of technology, data sources, algorithms, and sensors. Applied Science Intern, Corporate Projects US, WA, Seattle Amazon internships are full-time (40 hours/week) for 12 consecutive weeks with start dates in May - July 2023. Our internship program provides hands-on learning and building experiences for students who are interested in a career in hardware engineering. This role will be based in Seattle, and candidates must be willing to work in-person. Corporate Projects (CPT) is a team that sits within the broader Corporate Development organization at Amazon. We seek to bring net-new, strategic projects to life by working together with customers and evolving projects from ZERO-to-ONE. To do so, we deploy our resources towards proofs-of-concept (POCs) and pilot programs and develop them from high-level ideas (the ZERO) to tangible short-term results that provide validating signal and a path to scale (the ONE). We work with our customers to develop and create net-new opportunities by relentlessly scouring all of Amazon and finding new and innovative ways to strengthen and/or accelerate the Amazon Flywheel. CPT seeks an Applied Science intern to work with a diverse, cross-functional team to build new, innovative customer experiences. Within CPT, you will apply both traditional and novel scientific approaches to solve and scale problems and solutions. We are a team where science meets application. A successful candidate will be a self-starter comfortable with ambiguity, strong attention to detail, and the ability to work in a fast-paced, ever-changing environment. As an Applied Science Intern, you will own the design and development of end-to-end systems. You'll have the opportunity to create technical roadmaps, and drive production level projects that will support Amazon Science. You will work closely with Amazon scientists, and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. Data Scientist I - AMZ5920140 US, IL, Chicago MULTIPLE POSITIONS AVAILABLE Company: AMAZON.COM SERVICES LLC Position Title: Data Scientist I Location: Chicago, Illinois Position Responsibilities: Build the core intelligence, insights, and algorithms that support the real estate acquisition strategies for Amazon physical stores. Tackle cutting-edge, complex problems such as predicting the optimal location for new Amazon stores by bringing together numerous data assets, and using best-in-class modeling solutions to extract the most information out of them. Work with business stakeholders, software development engineers, and other data scientists across multiple teams to develop innovative solutions at massive scale. Amazon.com is an Equal Opportunity-Affirmative Action Employer - Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation #0000 [amazon-science-logo-whi] * About * Research areas * Blog * News and features * Publications * Conferences * Collaborations * Careers * Alexa Prize * Academics * Research Awards * Amazon Developer * Amazon Web Services * Newsletter * FAQs * RSS View from space of a connected network around planet Earth representing the Internet of Things. 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