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λ-Scaled-Attention: A Novel Fast Attention Mechanism for Efficient Modeling of Protein Sequences
Attention-based deep networks have been successfully applied on textual data in the field of NLP.
A novel model for query expansion using pseudo-relevant web knowledge
Among the three weighting models, tf-itf scores each of the individual terms obtained from the web content, kNN-based cosine similarity scores the expansion terms to obtain the term-term relationship, and correlation score weighs the selected expansion terms with respect to the whole query.
Pitch-Synchronous Single Frequency Filtering Spectrogram for Speech Emotion Recognition
On the other hand, the recently proposed single frequency filtering (SFF) spectrogram promises to be a better alternative because it captures both time and frequency resolutions simultaneously.
A new approach for query expansion using Wikipedia and WordNet
We also analyzed the effect on retrieval effectiveness of the proposed technique by varying the number of expansion terms.
Deep Robust Framework for Protein Function Prediction using Variable-Length Protein Sequences
The order of amino acids in a sequence enables a protein to acquire a particular stable conformation that is responsible for the functions of the protein.
DNN-HMM based Speaker Adaptive Emotion Recognition using Proposed Epoch and MFCC Features
Therefore, the information present in a speech such as message, emotion, language, speaker is due to the combined effect of both excitation source and vocal tract system.
Query expansion techniques for information retrieval: A survey
With the ever increasing size of the web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge.
