Speech and Song Search on the Web: System Design and Implementation

Yaguchi, Yuichi; Watanabe, Yu; Naruse, Keitaro; Oka, Ryuichi

doi:10.1109/cit.2007.128

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…In addition, we are planning to include a Web video retrieval system called 'AiZoom' [22] to retrieve more useful and reliable data from huge Web repositories.…”

Section: Discussionmentioning

confidence: 99%

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Yaguchi

Sakai

Yoshida

et al. 2009

2009 Ninth IEEE International Conference on Computer and Information Technology

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The clustering and recognition of Web video content play an important role in multimedia information retrieval. This paper proposes a method for both clustering and recognizing Web video content using a histogram of phoneme symbols (HoPS). HoPS contains information about speech and sound intervals. In this study, three experiments were conducted. The first experiment allocated HoPS feature of video intervals in a 3D space using PCA and quantification method IV (Q-IV). The second experiment applied the k-nearest neighbor (k-NN) method to analyze the difficulties in clustering. The third experiment recognized unknown video intervals by using the distance between HoPS of the query and a category average. The accuracy of the recognition results were 44.3% and 36.9% using the Mahalanobis distance and the correlation distance for the category average of training data, respectively.

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“…In addition, we are planning to include a Web video retrieval system called 'AiZoom' [22] to retrieve more useful and reliable data from huge Web repositories.…”

Section: Discussionmentioning

confidence: 99%

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Yaguchi

Sakai

Yoshida

et al. 2009

2009 Ninth IEEE International Conference on Computer and Information Technology

Self Cite

View full text Add to dashboard Cite

show abstract

“…In another example effort, the lattices of the query and the documents were aligned and compared using the graphical model [21]. People also tried to directly match the query and the content on the signal level [22], [23], as other examples. But clearly more work is needed for this task.…”

Section: Using Spoken Queries To Retrieve Spoken Documentsmentioning

confidence: 99%

Voice-based information retrieval — how far are we from the text-based information retrieval ?

Lee

Pan

2009

2009 IEEE Workshop on Automatic Speech Recognition &Amp; Understanding

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Although network content access is primarily text-based today, almost all roles of text can be accomplished by voice. Voice-based information retrieval refers to the situation that the user query and/or the content to be retried are in form of voice. This paper tries to compare the voice-based information retrieval with the currently very successful text-based information retrieval, and identifies two major issues in which voice-based information retrieval is far behind: retrieval accuracy and user-system interaction. These two issues are reviewed, analyzed and discussed in detail. It is found that very good approaches have been proposed and very good improvements have been achieved, although there is still a very long way to go. A few successful prototype systems, among many others are presented at the end.

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“…Continuous DP (CDP) [17], a wellknown spotting method, uses simultaneous recognition and segmentation, so there is no need to segment the input time sequence to be matched in advance. CDP has been applied to continuous sound [17,18] and gesture recognition [19]. It is superior to conventional DTW because it does not require pre-segmentation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Pixel Matching between Images

Yaguchi

Iseki

Oka

2009

Advances in Image and Video Technology

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Abstract.A two-dimensional continuous dynamic programming (2DCDP) method is proposed for two-dimensional spotting recognition of images. Spotting recognition is simultaneous segmentation and recognition of an image by optimal pixel matching between a reference and an input image. The proposed method performs optimal pixel-wise image matching and two-dimensional pixel alignment, which are not available in conventional algorithms. Experimental results show that 2DCDP precisely matches the pixels of non-linearly deformed images.

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Speech and Song Search on the Web: System Design and Implementation

Cited by 3 publications

References 9 publications

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Voice-based information retrieval — how far are we from the text-based information retrieval ?

Optimal Pixel Matching between Images

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Speech and Song Search on the Web: System Design and Implementation

Cited by 3 publications

References 9 publications

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Web Video Data Clustering and Recognition Using Histograms of Phoneme Symbols

Voice-based information retrieval &#x2014; how far are we from the text-based information retrieval ?

Optimal Pixel Matching between Images

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Product

Resources

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Voice-based information retrieval — how far are we from the text-based information retrieval ?