IBM Research-Haifa

Articles related to people and projects from IBM Research-Haifa.

New advances in speaker diarization

In a recent publication, “New Advances in Speaker Diarization,” presented virtually at Interspeech 2020, we describe our new state-of-the-art speaker diarization system that introduces several novel techniques.

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IBM Research AI at ICASSP 2020

The 45th International Conference on Acoustics, Speech, and Signal Processing is taking place virtually from May 4-8. IBM Research AI is pleased to support the conference as a bronze patron and to share our latest research results, described in nine papers that will be presented at the conference.

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High quality, lightweight and adaptable Text-to-Speech (TTS) using LPCNet

Recent advances in deep learning are dramatically improving the development of Text-to-Speech systems through more effective and efficient learning of voice and speaking styles of speakers and more natural generation of high-quality output speech.

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Four Papers Advance Computational Argumentation in IBM’s Project Debater

The latest work on computational argumentation from the IBM Project Debater research team group is being presented at the ACL 2019 conference. Three papers will be presented at the main conference and one more paper will be presented in the co-located Argument Mining Workshop.

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Label Set Operations (LaSO) Networks for Multi-Label Few-Shot Learning

Data augmentation is one of the leading methods to tackle the problem of few-shot learning, but current synthesis approaches only address the scenario of a single label per image, when in reality real life images may contain multiple objects. The IBM team came up with a novel technique for synthesizing samples with multiple labels.

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AI Models Predict Breast Cancer with Radiologist-Level Accuracy

Our team of IBM researchers published research in Radiology around a new AI model that can predict the development of malignant breast cancer in patients within the year, at rates comparable to human radiologists.

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RepMet: Representative-Based Metric Learning for Classification and Few-Shot Object Detection

Deep neural networks have demonstrated good results for few-shot learning. However, very few works have investigated the problem of few-shot object detection. A team of IBM researchers developed a novel approach for Distance Metric Learning (DML).

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Helping to Improve Medical Image Analysis with Deep Learning

Medical imaging creates tremendous amounts of data: many emergency room radiologists must examine as many as 200 cases each day, and some medical studies contain up to 3,000 images. Each patient’s image collection can contain 250GB of data, ultimately creating collections across organizations that are petabytes in size. Within IBM Research, we see potential in […]

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Video Scene Detection Using Optimal Sequential Grouping

Our team at IBM Research recently developed a new approach for automated video scene detection. Videos are used today for everything from entertainment and marketing to knowledge-sharing, news, and social journaling. Automated scene detection can help consumers and enterprises utilize this video content in new ways. Video scene detection is the task of temporally dividing […]

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Designing adaptive cyber-physical systems – from undersea monitoring to landing on Mars

Cyber-physical systems, or CPS for short, are sophisticated computer devices that work together to perform functions, control physical elements, and respond to human control. They are already being used in auto-pilot systems for aircraft, advanced robotic systems, smart grids, medical monitoring, and search and rescue. In fact, most Internet of Things (IoT) devices are CPS. […]

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IBM Fellow Awarded Levchin Prize for Contributions to Cryptography

We can all thank an elementary school teacher for keeping our electronic data safe and secure. Growing up in Argentina, and studying in Israel, not far from where his career started at IBM’s Haifa Lab, IBM Fellow and cryptographer, Hugo M. Krawczyk cites his third-grade teacher as one of his first influences. “She piqued my […]

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