5 citations · 18 across the 15 of their papers we have counts for
4 papers · 1 filter
Improving Named Entity Recognition in Telephone Conversations via Effective Active Learning with Human in the Loop
Md Tahmid Rahman Laskar, Cheng Chen, Xue-Yong Fu +1
Telephone transcription data can be very noisy due to speech recognition errors, disfluencies, etc. Not only that annotating such data is very challenging for the annotators, but a…
Entity-level Sentiment Analysis in Contact Center Telephone Conversations
Xue-Yong Fu, Cheng Chen, Md Tahmid Rahman Laskar +3
Entity-level sentiment analysis predicts the sentiment about entities mentioned in a given text. It is very useful in a business context to understand user emotions towards certain…
An Effective, Performant Named Entity Recognition System for Noisy Business Telephone Conversation Transcripts
Xue-Yong Fu, Cheng Chen, Md Tahmid Rahman Laskar +2
We present a simple yet effective method to train a named entity recognition (NER) model that operates on business telephone conversation transcripts that contain noise due to the…
BLINK with Elasticsearch for Efficient Entity Linking in Business Conversations
Md Tahmid Rahman Laskar, Cheng Chen, Aliaksandr Martsinovich +4
An Entity Linking system aligns the textual mentions of entities in a text to their corresponding entries in a knowledge base. However, deploying a neural entity linking system for…