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Our submission applying the phoneme based embedded segmental k-means model to the ZeroSpeech2017 challenge track 2. This is a preliminary version. More details can be found here: https://www.kamperh.com/papers/bhati+kamper+murty_icassp2018.pdf and https://github.com/Saurabhbhati/recipe_zs2017_track2
spoken term discovery, Zero resource speech processing, unsupervised learning
spoken term discovery, Zero resource speech processing, unsupervised learning
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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