In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.
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Question: We chose SVMhmm BIBREF111 implementation of Structural Support Vector Machines for sequence labeling. SVM implementation of
Question: Which machine learning methods are used in experiments?

Answer: Structural Support Vector Machine

Question: We explored different normalization techniques. FBanks with cepstral mean normalization (CMN) perform better than raw FBanks. We found using variance with mean normalization (CMVN) unnecessary for the task. Using deltas and delta-deltas improves model, so we used them in other experiments. Models trained with spectrogram features converge slower and to worse minimum, but the difference when using CMN is not very big compared to FBanks.
Question: What normalization techniques are mentioned?

Answer: FBanks with cepstral mean normalization (CMN) variance with mean normalization (CMVN)

Question: While many focus on giving a vector representation of a word, an increasing number now exist that will give a vector representation of a entire sentence or text. Following on from this work, we seek to devise a system that can run online, performing text clustering on the embeddings of texts one at a time
Question: How is an incoming claim used to retrieve similar factchecked claims?

Answer:
text clustering on the embeddings of texts