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Unsupervised spoken keyword spotting via segmental DTW on Gaussian posteriorgrams
In this paper, we present an unsupervised learning framework to address the problem of detecting spoken keywords. Without any transcription information, a Gaussian Mixture Model is trained to labelExpand
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Unsupervised Pattern Discovery in Speech
We present a novel approach to speech processing based on the principle of pattern discovery. Our work represents a departure from traditional models of speech recognition, where the end goal is toExpand
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Speech database development at MIT: Timit and beyond
Abstract Automatic speech recognition by computers can provide the most natural and efficient method of communication between humans and computers. While in recent years high performance speechExpand
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A probabilistic framework for segment-based speech recognition
Most current speech recognizers use an observation space based on a temporal sequence of measurements extracted from fixed-length ‘‘frames’’ (e.g., Mel-cepstra). Given a hypothetical word or sub-wordExpand
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Highway long short-term memory RNNS for distant speech recognition
In this paper, we extend the deep long short-term memory (DL-STM) recurrent neural networks by introducing gated direct connections between memory cells in adjacent layers. These direct links, calledExpand
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Unsupervised Learning of Disentangled and Interpretable Representations from Sequential Data
We present a factorized hierarchical variational autoencoder, which learns disentangled and interpretable representations from sequential data without supervision. Specifically, we exploit theExpand
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JUPlTER: a telephone-based conversational interface for weather information
In early 1997, our group initiated a project to develop JUPITER, a conversational interface that allows users to obtain worldwide weather forecast information over the telephone using spokenExpand
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Robust Speaker Recognition in Noisy Conditions
This paper investigates the problem of speaker identification and verification in noisy conditions, assuming that speech signals are corrupted by environmental noise, but knowledge about the noiseExpand
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A Nonparametric Bayesian Approach to Acoustic Model Discovery
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneously segments theExpand
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SemEval-2016 Task 3: Community Question Answering
This paper describes the SemEval–2016 Task 3 on Community Question Answering, which we offered in English and Arabic. For English, we had three subtasks: Question–Comment Similarity (subtask A),Expand
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