On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,742 papers · 148 categories

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4 results for “Bengali”

A Hybrid Approach Towards Two Stage Bengali Question Classification Utilizing Smart Data Balancing Techniquecs.CL

Hybrid QC system for Bengali questions using smart data balancing.

problem Classifying factoid questions in Bengali.

method Two-stage approach with 1D CNN for coarse classification and SGD for fine classification.

result Effectiveness of smart data balancing technique in improving classification accuracy.

Bengali Question Classification Hybrid Approach Smart Data Balancing Convolutional Neural Network

2019-11-30abs ↗pdf ↗

On Stacked Denoising Autoencoder based Pre-training of ANN for Isolated Handwritten Bengali Numerals Dataset Recognitioncs.LG

This work attempts to find the most optimal parameter setting of a deep artificial neural network (ANN) for Bengali digit dataset by pre-training it using stacked denoising autoencoder (SDA). Although SDA based recognition is hugely popular in image, speech and language processing related tasks among the researchers, i…

2018-12-14abs ↗pdf ↗

Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Networkcs.CL

Paper benchmarks Bengali language classification tasks using MConv-LSTM network.

problem Lack of computational resources for NLP tasks in under-resourced languages like Bengali.

method Built three datasets, BengFastText word embeddings, and MConv-LSTM network for hate speech detection, document classification, and sentiment analysis.

result BengFastText yields up to 92.30%, 82.25%, and 90.45% F1-scores in document classification, sentiment analysis, and hate speech detection respectively.

Bengali Multichannel Convolutional-LSTM Hate Speech Sentiment Analysis Document Classification

2020-04-11abs ↗pdf ↗

Language-agnostic Multilingual Modelingeess.AS

New ASR system handles multiple languages without needing language-specific encoding.

problem Joint training of data-rich and data-scarce languages in a single model.

method Transforms all languages to a single writing system through transliteration, separating modeling and rendering.

result Language-agnostic multilingual ASR system reduces WER up to 10% over language-dependent models.

Multilingual ASR Language-independent Transliteration Canonical target sequence Word Error Rate

2020-04-20abs ↗pdf ↗