Search Results for author:
Found 13 papers, 7 papers with code
Adaptive Discounting of Implicit Language Models in RNN-Transducers
RNN-Transducer (RNN-T) models have become synonymous with streaming end-to-end ASR systems.
Multi-Row, Multi-Span Distant Supervision For Table+Text Question
Question answering (QA) over tables and linked text, also called TextTableQA, has witnessed significant research in recent years, as tables are often found embedded in documents along with related text.
Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages
We hypothesize and validate that multilingual fine-tuning of pre-trained language models can yield better performance on downstream NLP applications, compared to models fine-tuned on individual languages.
Multiple Choice Question Answering (MCQA)
Natural Language Inference
+3
Topic Transferable Table Question Answering
Weakly-supervised table question-answering(TableQA) models have achieved state-of-art performance by using pre-trained BERT transformer to jointly encoding a question and a table to produce structured query for the question.
Representation based meta-learning for few-shot spoken intent recognition
Spoken intent detection has become a popular approach to interface with various smart devices with ease.
AIT-QA: Question Answering Dataset over Complex Tables in the Airline Industry
Recent advances in transformers have enabled Table Question Answering (Table QA) systems to achieve high accuracy and SOTA results on open domain datasets like WikiTableQuestions and WikiSQL.
Capturing Row and Column Semantics in Transformer Based Question Answering over Tables
While this model yields extremely high accuracy at finding cell values on recent benchmarks, a second model we propose, called RCI representation, provides a significant efficiency advantage for online QA systems over tables by materializing embeddings for existing tables.
Disfluency Correction using Unsupervised and Semi-supervised Learning
Spoken language is different from the written language in its style and structure.
Multilingual and code-switching ASR challenges for low resource Indian languages
For this purpose, we provide a total of ~600 hours of transcribed speech data, comprising train and test sets, in these languages including two code-switched language pairs, Hindi-English and Bengali-English.
Addressing target shift in zero-shot learning using grouped adversarial learning
Zero-shot learning (ZSL) algorithms typically work by exploiting attribute correlations to be able to make predictions in unseen classes.
REVISTING NEGATIVE TRANSFER USING ADVERSARIAL LEARNING
An unintended consequence of feature sharing is the model fitting to correlated tasks within the dataset, termed negative transfer.
A deep learning approach to solar-irradiance forecasting in sky-videos
Ahead-of-time forecasting of incident solar-irradiance on a panel is indicative of expected energy yield and is essential for efficient grid distribution and planning.
Future semantic segmentation of time-lapsed videos with large temporal displacement
An important aspect of video understanding is the ability to predict the evolution of its content in the future.
