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Unsupervised query-by-example spoken term detection based on DPHMM tokenizer

2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), 2017
This paper investigates the use of Dirichlet process hidden Markov model (DPHMM) tokenizer for the template matching based query-by-example spoken term detection (QbE-STD) task. DPHMM can be obtained following an unsupervised iterative procedure without any training transcriptions. The STD performance of the DPHMM tokenizer is evaluated on TIMIT Corpus.
Cao Jiankai, Lianhai Zhang
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CNN-based bottleneck feature for noise robust query-by-example spoken term detection

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2017
This paper addresses the problem of query-by-example spoken term detection (QbE-STD) in the presence of background noises that are inevitable in real applications. To deal with this, we propose a convolutional neural network (CNN) based bottleneck feature representation for a keyword.
Hyungjun Lim, Younggwan Kim, Yoonhoe Kim, Hoirin Kim   +3 more
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Design of mixture of GMMs for Query-by-Example Spoken Term Detection

Computer Speech & Language, 2018
Abstract This paper presents the design of a mixture of Gaussian Mixture Models (GMMs) for Query-by-Example Spoken Term Detection (QbE-STD). The speech data governs acoustically similar broad phonetic structures. To capture broad phonetic structure, we exploit additional information of broad phoneme classes (such as vowels, semi-vowels, nasals ...
Maulik C. Madhavi, Hemant A. Patil
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Multilingual query-by-example spoken term detection in Indian languages

International Journal of Speech Technology, 2019
Spoken language processing poses to be a challenging task in multilingual and mixlingual scenario in linguistically diverse regions like Indian subcontinent. Common articulatory based framework is explored for the representation of phonemes of different languages.
Abhimanyu Popli, Arun Kumar
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Combining evidences from detection sources for query-by-example spoken term detection

2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2017
The objective of this paper is to explore various detection cues for Query-by-Example Spoken Term Detection (QbE-STD) system. Under template matching paradigm, Dynamic Time Warping (DTW) has been used extensively for QbE-STD task. DTW detection score relies on the alignment of features w.r.t. query and test utterance.
Maulik C. Madhavi, Hemant A. Patil
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Query-by-Example Spoken Term Detection using Attentive Pooling Networks

2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2019
Query-by-example spoken term detection (QbE-STD) is attractive because its a key technology for retrieving and browsing spoken content without transcribing them into text. Several end-to-end models based on encoder architecture have been proposed for QbE-STD, in which the input pair, spoken query and audio segment, are first projected into fixed-length
Binheng Song, Zhiyong Wu, Jia Jia, Kun Zhang, Helen Meng   +4 more
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Effective utilization of multiple examples in query-by-example spoken term detection

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016
This paper investigates the example utilization problem in query-by-example spoken term detection when multiple examples are provided for each query term. To achieve this goal, we propose three evaluation metrics to assess the quality of all the examples, namely posteriorgram stability score, pronunciation reliability score and local similarity score ...
Ji Xu, Yonghong Yan, Ge Zhang
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Siamese Recurrent Auto-Encoder Representation for Query-by-Example Spoken Term Detection

Interspeech 2018, 2018
Ziwei Zhu, Zhiyong Wu, Runnan Li, Helen Meng, Lianhong Cai   +4 more
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Query-by-example spoken term detection using phonetic posteriorgram templates

2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 2009
This paper examines a query-by-example approach to spoken term detection in audio files. The approach is designed for low-resource situations in which limited or no in-domain training material is available and accurate word-based speech recognition capability is unavailable.
Christopher White, Timothy J. Hazen, Wade Shen   +2 more
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Multilingual query by example spoken term detection for under-resourced languages

2013 7th Conference on Speech Technology and Human - Computer Dialogue (SpeD), 2013
We propose a query-by-example approach to multilingual Spoken Term Detection for under-resourced languages based on Automatic Speech Recognition. The approach overcomes the main difficulties met under these conditions, i.e., providing a new method for building multilingual acoustic models with few annotated data and searching in approximate Automatic ...
Mihai Safta, Andi Buzo, Horia Cucu, Corneliu Burileanu   +3 more
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