Customer-obsessed science
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February 2, 202610 min readEvery NFL game generates millions of tracking data points from 22 RFID-equipped players. Seventy-five machine learning models running on AWS process that data in under a second, transforming football into a sport where every movement is measured, modeled, and instantly analyzed.
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January 13, 20267 min read
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January 8, 20264 min read
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December 29, 20256 min read
Featured news
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2024In the realm of spoken language understanding (SLU), numerous natural language understanding (NLU) methodologies have been adapted by supplying large language models (LLMs) with transcribed speech instead of conventional written text. In real-world scenarios, prior to input into an LLM, an automated speech recognition (ASR) system generates an output transcript hypothesis, where inherent errors can degrade
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2024Recent advancements in Generative AI, such as scaled Transformer large language models (LLM) and diffusion decoders, have revolutionized speech synthesis. With speech encompassing the complexities of natural language and audio dimensionality, many recent models have relied on autoregressive modeling of quantized speech tokens. Such an approach limits speech synthesis to left-to-right generation, making
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CHIIR 20242024To help customers who are still in the exploration phase, Web search engines and e-commerce websites often provide relevant Q&As in widgets, such as ‘People Also Ask’ and ‘Customers Also Ask Alexa’, with additional information. In this work, we propose to enrich this customer experience by rendering related products under each Q&A based on an automated online query recommendation. We define what are the
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AAAI 2024 Workshop on Scientific Document Understanding2024Watermark text spotting in document images can offer access to an often unexplored source of information, providing crucial evidence about a record’s scope, audience and sometimes even authenticity. Stemming from the problem of text spotting, detecting and understanding watermarks in documents inherits the same hardships - in the wild, writing can come in various fonts, sizes and forms, making generic recognition
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2024While word error rates of automatic speech recognition (ASR) systems have consistently fallen, natural language understanding (NLU) applications built on top of ASR systems still attribute significant numbers of failures to low-quality speech recognition results. Existing assistant systems collect large numbers of these unsuccessful interactions, but these systems usually fail to learn from these interactions
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