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Unsupervised Speech Processing with Applications to Query-by-Example Spoken Term Detection [PDF]
, 2013 Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p.
Yaodong Zhang
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A fast query-by-example spoken term detection for zero resource languages
2016 International Conference on Signal Processing and Communications (SPCOM), 2016This paper presents a novel two-pass dynamic time warping (DTW) approach to build Query-by-Example Spoken Term Detection (QbE-STD) system for Zero Resource Languages. An unconstrained-endpoint dynamic time warping (UE-DTW) algorithm is used to locate the query term occurrences in a long conversational audio.
Karthik Pandia D S +2 more
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A Stage Match for Query-by-Example Spoken Term Detection Based On Structure Information of Query
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021The state-of-the-art of query-by-example spoken term detection (QbE-STD) strategies are usually based on segmental dynamic time warping (S-DTW). However, the sliding window in S-DTW may separate signal of a word into different segments and produce many illegal candidates required to be compared with the query, which significantly reduce the accuracy ...
Su Jianbin +3 more
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Query-by-Example Spoken Term Detection Evaluation on Low-Resource Languages
2014As part of the MediaEval 2013 benchmark evaluation campaign, the objective of the Spoken Web Search (SWS) task was to perform Query-by-Example Spoken Term Detection (QbE-STD), using spoken queries to retrieve matching segments in a set of audio files. As in previous editions, the SWS 2013 evaluation focused on the development of technology specifically
Miro, Xavier Anguera +5 more
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Memory efficient subsequence DTW for Query-by-Example Spoken Term Detection
2013 IEEE International Conference on Multimedia and Expo (ICME), 2013In this paper we propose a fast and memory efficient Dynamic Time Warping (MES-DTW) algorithm for the task of Query-by-Example Spoken Term Detection (QbE-STD). The proposed algorithm is based on the subsequence-DTW (S-DTW) algorithm, which allows the search for small spoken queries within a much bigger search collection of spoken documents by ...
Miquel Ferrarons, Xavier Anguera
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Phonetic unit selection for cross-lingual query-by-example spoken term detection
2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2015Cross-lingual query-by-example spoken term detection (QbE STD) has caught the attention of speech researchers, as it makes it possible to develop systems for low-resource languages, in which the available amount of labelled data makes the training of automatic speech recognition approaches prohibitive.
Carmen García-Mateo +2 more
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A Refined Query-by-Example Approach to Spoken-Term-Detection on ESL learners’ Speech
2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP), 2018A refined Query-by-Example (QbE) approach is proposed to improve Spoken-Term-Detection (STD) performance on L2 English learners’ speech data. A Hidden Markov Model (HMM) is built for each keyword and a computationally efficient, iterative Viterbi decoding is adopted to detect spoken keywords in test.
Jingyong Hou +3 more
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Analysis of constraints on segmental DTW for the task of query-by-example spoken term detection
2015 Annual IEEE India Conference (INDICON), 2015Query-by-example spoken term detection (QbE-STD) refers to the task of determining the subsequence of a reference which matches with a query, where both the query and the reference are in audio format. Dynamic time warping (DTW) based techniques are explored to match the two sequences with different lengths in an unsupervised manner.
Sri Harsha Dumpala +3 more
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Query-by-Example Spoken Term Detection System Based on Phoneme Posterior Features [PDF]
2017 International Conference on Computer Technology, Electronics and Communication (ICCTEC), 2017 Spoken term detection (STD) provides an efficient means for keyword indexing of speech. However, achieving high detection performance, fast speed, detecting out-of-vocabulary (OOV) words and performing STD on low resource languages are some of the major research challenges.
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Multitask Feature Learning for Low-Resource Query-by-Example Spoken Term Detection
IEEE Journal of Selected Topics in Signal Processing, 2017We propose a novel technique that learns a low-dimensional feature representation from unlabeled data of a target language, and labeled data from a nontarget language. The technique is studied as a solution to query-by-example spoken term detection (QbE-STD) for a low-resource language.
Hongjie Chen +4 more
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